PLEASE SCROLL DOWN FOR ARTICLE

This article was downloaded by: [Faroqi-Shah, Yasmeen]On: 28 February 2011Access details: Access Details: [subscription number 934167649]Publisher Psychology PressInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

AphasiologyPublication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t713393920

Investigation of self-monitoring in fluent aphasia with jargonMonica Sampsona; Yasmeen Faroqi-Shaha

a University of Maryland, College Park, MD, USA

First published on: 29 November 2010

To cite this Article Sampson, Monica and Faroqi-Shah, Yasmeen(2011) 'Investigation of self-monitoring in fluent aphasiawith jargon', Aphasiology, 25: 4, 505 — 528, First published on: 29 November 2010 (iFirst)To link to this Article: DOI: 10.1080/02687038.2010.523471URL: http://dx.doi.org/10.1080/02687038.2010.523471

Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf

This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden.

The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.

APHASIOLOGY, 2011, 25 (4), 505–528

Investigation of self-monitoring in fluent aphasia with jargon

Monica Sampson and Yasmeen Faroqi-ShahUniversity of Maryland, College Park, MD, USA

Background: Some individuals with fluent aphasia produce jargon errors in speech pro-duction. Jargon likely results from derailed encoding operations required for languageproduction, although the exact mechanism remains debated. It is also unclear if personswho produce jargon are able to self-monitor; that is, detect the non-word status of theirimminent utterance and self-correct the error.Aims: This study investigated the characteristics of speech monitoring in individuals withfluent aphasia who produce jargon. The association of speech monitoring with amountof jargon produced and success in auditory comprehension was examined. Further, therole of post-articulatory auditory feedback on speech-monitoring success was examinedby introducing an auditory masker (white noise). Finally, the influence of task demandson amount of jargon and speech monitoring was examined.Methods & Procedures: Five individuals with fluent aphasia with jargon participated inthe study. Speech monitoring was tested using three production tasks (picture naming,non-word repetition, and word repetition) under two listening conditions (normal listen-ing and masking noise). Speech-monitoring score was derived from self-judgements ofproduction accuracy. Auditory processing was examined in speech discrimination, lexicaldecision, and single-word identification tasks.Outcomes & Results: Results indicated that severity of self-monitoring impairment is: (1)strongly correlated with severity of jargon production, (2) poorly correlated with auditoryprocessing abilities, (3) worse under masking noise, and (4) worse for naming comparedto repetition.Conclusions: Overall, all five participants with jargon demonstrated severely impairedspeech monitoring under both listening conditions across all three production tasks, sug-gesting that the role of speech-monitoring impairment in jargon cannot be disregarded.The increase in amount of jargon and severity of speech-monitoring failure with increasedlinguistic demands of the production task (as in picture naming and non-word repeti-tion) raises the possibility of a post-semantic deficit in accessing phonological codes. Thispossible locus of deficit, and implications for understanding production of jargon, arediscussed.

Keywords: Jargon; Aphasia; Self-monitoring; Feedback; Comprehension; Lexical-phonological encoding.

Address correspondence to: Monica Sampson, Department of Hearing and Speech Sciences, Universityof Maryland, 0133 Lefrak Hall, College Park, MD – 20742, USA. E-mail: msampson@hesp.umd.edu

This work was supported by the MCM Fund for Student Research Excellence to the first author fromthe Department of Hearing and Speech Sciences, University of Maryland, College Park. The authors wishto thank all the participants and their families for their participation and support for this research. We alsoacknowledge the assistance of Lauren Graham and Lisa Pyun in transcription and data analysis. We aregrateful to two anonymous reviewers for their helpful comments on earlier versions of the manuscript.

The findings of this study were presented at the Annual Convention of the American Speech Languageand Hearing Association (2009).

© 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa businesshttp://www.psypress.com/aphasiology DOI: 10.1080/02687038.2010.523471

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

506 SAMPSON AND FAROQI-SHAH

Self-monitoring is the process of checking one’s own speech for linguistic accuracy,identifying errors, and initiating repairs. The speech of some individuals with fluentaphasia is marked by “jargon” errors. The definition of what constitutes “jargon” hasvaried widely in the literature (e.g., Marshall, 2006), ranging from semantically relatedor unrelated real-word errors (e.g., plate or book for fork; e.g., Marshall, Pring, Chiat,& Robson, 1996), phonologically related errors (e.g., cork or /θOrk/ for fork; e.g.,Kohn, Smith, & Alexander, 1996) to unrelated non-words (e.g., /blaIn/ for fork; e.g.,Butterworth, 1979, 1985; Moses, Nickels, & Sheard, 2004; Robson, Pring, Marshall,& Chiat, 2003). In this paper we use the term “jargon” to refer to errors produced byindividuals with fluent aphasia, encompassing semantically/phonologically unrelatedreal-word errors as well as phonologically related and unrelated non-word errors.

Individuals with fluent aphasia who produce jargon errors have also been frequentlyreported to attempt few corrections of these self-generated speech errors, suggestinga possible self-monitoring deficit (Ellis, Miller, & Sin, 1983; Hanlon & Edmonson,1996; Kohn et al., 1996; Maher, Gonzalez-Rothi, & Heilman, 1994; Marshall, 2006;Marshall, Robson, Pring, & Chiat, 1998; Nickels & Howard, 1995; Shuren, Smith-Hammond, Maher, Rothi, & Heilman, 1995). However, a few other studies havedocumented an ability to detect speech errors (Robson, Marshall, Pring, & Chiat,1999) and sometimes repair them depending on the production task employed (Moseset al., 2004). A participant with fluent aphasia in whom jargon production was tem-porarily induced by sodium amytal injection also reported partial awareness of speecherrors (Lazar, Marshall, Prell, & Pile-Spellman, 2000). Hence prior studies presentconflicting evidence on the co-occurrence and role of impaired self-monitoring in theproduction of jargon. This study sought to examine if self-monitoring is impairedin individuals with fluent aphasia producing jargon errors (henceforth FAJ) irrespec-tive of other language characteristics. Given the differing definitions of jargon in theliterature, in this study jargon is operationally defined as consisting of either non-word errors (neologisms and phonemic jargon) or semantically unrelated real-worderrors (semantic jargon) in fluent spontaneous speech. It excludes the stereotypicalutterances produced by some individuals with global aphasia, which are of extremelylimited variety.

The psycholinguistic framework used in the present study is provided here as acontext for the hypotheses and experimental tasks. Most psycholinguistic theoriesof speech production suggest that at least two components are involved in self-monitoring: a feedback mechanism and a monitor (see review in Postma, 2000).Self-monitoring is proposed to begin with the encoded information being fed backinto the monitor via two possible routes (Hartsuiker & Kolk, 2001, Levelt, 1983,1989; see review by Postma, 2000). A pre-articulatory feedback route is assumedto feed the phonologically encoded signal into the monitor—loop (a) in Figure 1(Roelofs, 2005; Wheeldon & Levelt, 1995). This pre-articulatory loop is assumed toinitiate covert repairs such as hesitations, pauses, and part-word repetitions in nor-mal speakers (Kolk, 1995; Levelt 1983, 1989; Oomen, Postma, & Kolk, 2001; Postma& Kolk, 1993). A post-articulatory feedback route is assumed to channel overtly pro-duced utterances to the monitor by means of auditory and articulatory-proprioceptiveinformation—loop (b) in Figure 1 (Hartsuiker & Kolk, 2001; Levelt, 1983, 1989;Schiller, 2005; Wheeldon & Levelt, 1995). Overtly produced errors and repairs suchas lexical/phonological/syntactic revisions are argued to be indicative of the function-ing of the post-articulatory feedback route (Hartsuiker, Kolk & Martensen, 2005).

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 507

Message Generation

Lexical-Semantic Processing

Phonological Encoding

Phonological Buffer

Articulation

Single Word Identification

Auditory Lexical

Decision

Speech Discrimination

Monitor

Error Detection

Error Correction

Error Detection Error Correction

Error Detection Error Correction

Error Detection Error Correction

Error Detection Error Correction

(a)

(b)

Figure 1. Relationship between input and output linguistic processes involved in self-monitoring mecha-nism: (a) refers to the pre-articulatory monitoring loop; (b) refers to the post-articulatory monitoring loop.The dotted circles represent hypothesised locations of the production-based monitors and the solid linecircles represent the hypothesised location of the perception-based monitor. Adapted from Levelt (1983,1989).

Analysis of covert and overt errors and their repairs is one method used to teaseapart the contribution of pre- and post-articulatory feedback loops in neurologicallyunimpaired speakers (Levelt 1983, 1989; Kolk, 1995; Oomen et al., 2001; Postma &Kolk, 1993; Schlenck, Huber, & Wilmes, 1987). Although such analyses might be suit-able for unimpaired speakers, the interpretation of covert versus overt repairs is notstraightforward for aphasic speech because hesitations and repairs could occur dueto problems in the linguistic mechanism that are unrelated to feedback, such as wordretrieval deficits (Nickels & Howard, 1995). Therefore impairments in feedback loopswill need to be examined with alternate analyses. Even though experimental manipu-lation of pre-articulatory feedback is not straightforward, the relative contribution ofthe post-articulatory route can be examined by altering auditory feedback. This canbe done using either delayed auditory feedback or masking noise.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

508 SAMPSON AND FAROQI-SHAH

Prior studies with altered auditory feedback in individuals with FAJ have foundconflicting results. Peuser and Temp (1981) found that the speech of individuals withfluent aphasia was unaffected by delayed auditory feedback (unlike neurologicallyunimpaired speakers who become considerably dysfluent). Contrary to these findings,Maher et al. (1994) reported greater dysfluency and improved self-monitoring in a par-ticipant with FAJ with intact comprehension under delayed auditory feedback. Veryfew studies have systematically examined the possible impact of impaired feedback onself-monitoring in individuals with jargon aphasia and, to our knowledge, auditorymasking has not been used with this population (although Oomen et al., 2001, usedmasking noise in Broca’s aphasia). In the current study, masking noise was introducedduring verbal productions to limit the individual’s access to external auditory feed-back. The assumption is that if individuals with FAJ have a severe breakdown in thepost-articulatory feedback route, then altering their auditory feedback is unlikely tochange self-monitoring performance relative to normal listening conditions.

Another possible locus of self-monitoring breakdown in individuals with jargonerror production is the monitor itself. The “monitor” is a construct used to refer tothe mental process that compares the generated linguistic code to the intended targetto detect inconsistencies (Hartsuiker & Kolk, 2001; Hartsuiker, Bastiaanse, Postma,& Wijnen, 2005; Levelt, 1983, 1989). If an error is detected, then the monitor is pro-posed to initiate repairs as necessary. Thus the monitor is postulated to include errordetection and repair initiation components (Blackmer & Mitton, 1991; De Smedt &Kempen, 1987; Hartsuiker & Kolk, 2001; Laver, 1980; Levelt, 1989; Oomen & Postma,2001; Postma & Oomen, 2005; van Wijk & Kempen, 1987). Therefore, a breakdown inone or a combination of these components could impact self-monitoring capabilities.

The nature of the monitor has largely been unspecified and its reliance on auditorycomprehension has been extensively debated (Postma, 2000). Two types of moni-tors have been postulated in the literature: production-based and perception-based.Production-based monitors have been suggested to function with little to no relianceon auditory comprehension (Postma, 2000). These are proposed to have direct accessto the individual sub-components of speech production processes (De Smedt &Kempen, 1987; Laver, 1973, 1980; Schlenk et al., 1987; van Wijk & Kempen, 1987)allowing intact self-monitoring even in the presence of impaired auditory comprehen-sion (Lazar et al., 2000; Moses et al., 2004; Robson et al., 1999). Production-basedmonitors are hypothesised to be either distributed (where each processing level hasits own monitor to detect/correct errors; Laver, 1973, 1980; Schlenk et al., 1987) orcentral (where the monitor is centrally located with distributed loops feeding in infor-mation from intermediate levels of language encoding; De Smedt & Kempen, 1987;van Wijk & Kempen, 1987).

The perception-based monitor, first proposed by Levelt’s perceptual loop theory(Levelt, 1983, 1989), strongly relies on input language-processing mechanisms foranalysis of the code from pre-articulatory and post-articulatory feedback (Figure 1).The output of this analysis (involving discrimination, lexical decision, and compre-hension) would then be compared to the intended code, by the monitor, to initiate anyrequired repairs. Therefore the success of both pre- and post-articulatory monitor-ing (involving error detection and repair) is extensively dependent on the integrity ofthe auditory comprehension mechanism in a perception-based monitor (Levelt, 1983,1989; Hartsuiker & Kolk, 2001). Since significant comprehension deficits are oftenreported in individuals with FAJ, it is therefore possible that auditory comprehen-sion impairments could influence error detection and repair (Butterworth, 1979; Ellis

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 509

et al., 1983; Hillis, Boatman, Hart, & Gordon, 1999; Maneta, Marshall, & Lindsay,2001). Marshall, Neuberger, and Phillips (1994) offer some evidence for this relation-ship. In their investigation of self-repair in individuals with aphasia, they found thatthose individuals with highest comprehension scores repaired the highest number oferrors. Also, those individuals with better comprehension demonstrated higher gainsin treatment of self-monitoring deficits.

However, several other findings undermine this relationship between self-monitoring and comprehension impairments in individuals with FAJ (Marshall,Rappaport, & Garcia-Bunuel, 1985; Marshall et al., 1998; Nickels & Howard, 1995;Schlenck et al., 1987). Marshall et al. (1985) described an individual with severeauditory comprehension deficits who was acutely aware of her errors and made fre-quent, but unsuccessful, attempts to self-correct her productions. Marshall et al.(1998) demonstrated a double dissociation between monitoring self-generated jargon(in naming, repetition, and reading) and auditory comprehension: two of their partic-ipants demonstrated poor self-monitoring in all tasks despite intact comprehension,while a third participant demonstrated good awareness of his speech errors despitepoor auditory comprehension. Nickels and Howard (1995) and Schlenck et al. (1987)also report an inconsistency between self-monitoring and auditory comprehensionabilities. Most prior studies elicited speech (in which self-monitoring was examined)and tested auditory processing using different stimuli sets; that is, a patient might havebeen unimpaired in auditorily processing a specific lexical item, but that specific itemwas not elicited in the spoken task for examination of self-monitoring. This under-mines the conclusion of dissociation between these two factors because item-specificimpairments could not be ruled out. Hence the relationship between auditory process-ing and self-monitoring abilities needs further examination with particular attentionto using the same lexical items to examine auditory processing and self-monitoring ofone’s own speech.

This study investigated the extent of the relationship between self-monitoring andauditory-processing abilities of individuals with FAJ using the same stimuli for inputand output processing tasks. Self-monitoring (detection and correction of one’s ownerrors) was examined for picture naming, non-word repetition, and word repetitiontasks. As mentioned earlier, the question of auditory processing impairments of thispatient population is relevant because of the notion that pre- and post-articulatoryself-monitoring is perception based (Levelt, 1989). In this study auditory processingabilities were examined using three tasks: speech discrimination, lexical decision, andsingle-word identification. The speech discrimination task explores integrity of lower-level auditory processing using both word and non-word stimuli pairs (e.g., cug–cugversus cup–cug). The lexical decision task taps access to the auditory input lexiconwithout demands on semantic processing (Marshall et al., 1998). Also, the ability todetect non-words in the task would reflect the participant’s ability to identify jargonerrors. The single-word identification task involving spoken word to picture matchingtests the entire auditory comprehension pathway at the word level including access tosemantic representations. Absence of correlation or a weak correlation between self-monitoring and auditory processing would suggest that auditory processing abilitiesdo not significantly contribute to self-monitoring.

Besides the influence of auditory processing abilities on error monitoring in self-generated speech, self-monitoring deficits in individuals with FAJ could also beexamined by a direct analysis of their error detection or error repair skills. Typicalmeasures of error detection (such as analysis of error/repair type in neurologically

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

510 SAMPSON AND FAROQI-SHAH

unimpaired speakers) pose difficulties in interpretation of self-monitoring abilitiesin individuals with aphasia secondary to their word retrieval deficits. Therefore, theclosest alternate indicator of error awareness is participants’ self-report of produc-tion accuracy (Maher at al., 1994; Shuren et al, 1995). Error correction abilities, onthe other hand, can be evaluated by examining the number and success of attemptsat self-correction of productions. If error correction deficits are associated withself-monitoring impairments in these individuals with jargon production, then par-ticipants’ success of error detection in all tasks would be expected to be better thansuccess of error repair, irrespective of task demands. But if participants’ deficits stemfrom poor awareness of errors produced, then error detection is not expected to bebetter than error correction.

Additionally, evidence suggests that severity of jargon and monitoring failure mayincrease with increasing word production demands (Marshall, 2006; Marshall et al.,1998). For example, Marshall et al.’s (1998) study found that individuals with FAJwere poorer in self-monitoring responses to picture naming compared to word repe-tition. Given that picture naming and repetition differ primarily in the availability ofphonological information, it was suggested that the process of retrieving the phono-logical code after lexical selection is impaired. If jargon is produced because of partialor complete unavailability of phonological information in picture naming, then con-sequently the patient fails in self-monitoring because there is an impoverished or nophonological model for comparison of intended and produced utterances. Conversely,self-monitoring is better and less jargon would be produced in repetition tasks becauseof the availability of phonological information. This argument was further substanti-ated by Marshall et al. (1998) by examining the patient’s self-monitoring after trainingthe patient to link semantic and phonological information of specific items. Thistraining appeared to have a significant effect in improving the patient’s error detec-tion. These findings imply that self-monitoring possibly depends on the nature of theproduction task and the language encoding demands that it entails.

In the current study, jargon production and self-monitoring of errors were exam-ined using three production tasks of increasing encoding demands: picture naming,non-word repetition, and word repetition. Picture naming relies on the participation ofthe word production system including concept selection, lemma retrieval, phonolog-ical encoding (phonological lexical retrieval and post-lexical phonological encoding),phonological buffer, and articulation (Levelt, 1983, 1989). Both non-word and wordrepetition involve sublexical processing and require phonological encoding. However,neither non-word nor word repetition necessarily rely on lexical retrieval. In non-wordrepetition the speaker needs to assemble the phonological information of individualphonemes obtained from the model into unfamiliar sequences, while increased acti-vation from prior semantic knowledge for real words reduces the demands in wordrepetition. It was hypothesised that if lexical retrieval failure results in self-monitoringbreakdown, then participants’ performance (production accuracy, error detection,and error correction) should be better in repetition (word and non-word) than inpicture naming where the target needs to be generated.

To summarise, the evidence for impaired self-monitoring as the source of jar-gon in individuals with FAJ is inconclusive and needs further investigation. Threeaspects of this relationship are particularly interesting and relevant. First, previousinvestigations have not clearly delineated the role of pre- versus post-articulatoryfeedback in self-monitoring failure in individuals with jargon production. Second,the relationship between self-monitoring and auditory comprehension deficits needs

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 511

further examination. It is not known if any particular auditory processing level(discrimination, lexical decision, or comprehension) is related to self-monitoring.Finally, it is not clear from available research evidence if varying linguistic encod-ing demands, such as in naming versus repetition, have a differential impact on thesuccess of self-monitoring. Each of these aspects was evaluated in the current studyusing three production tasks (picture naming, non-word repetition, and word repeti-tion) under two listening conditions (normal auditory feedback and masking noise)and three auditory processing tasks (speech discrimination, auditory lexical decision,and single-word identification). Those individuals with aphasia who produced jar-gon errors in spontaneous speech during initial language testing were included inthe study, irrespective of their auditory comprehension skills or speech error moni-toring abilities. Participants’ self-monitoring and jargon production were examinedusing self-monitoring scores and jargon scores (described under Method). The roleof post-articulatory feedback was examined by comparing success of self-monitoringunder normal listening condition and masking noise. It was predicted that if individ-uals with FAJ had a significant deficit in post-articulatory auditory feedback, then nosignificant change in self-monitoring would be noted when comparing performancewith and without masking noise. The impact of a possible auditory comprehensiondeficit on the success of self-monitoring was examined by correlations between accu-racy of single-word comprehension and monitoring scores (in picture naming undernormal listening). It was also predicted that greater correspondence than discrepancybetween performances on these two tasks in an item analysis would reflect an associ-ation between auditory processing and self-monitoring. Finally, the role of linguisticencoding complexity of production tasks on self-monitoring was examined by com-paring success of self-monitoring in picture naming, non-word repetition, and wordrepetition.

METHOD

Participants

Five participants were recruited for the study (age range: 59–79 years). All partici-pants provided written consent per approved guidelines of the Institutional ReviewBoard at the University of Maryland, College Park. Participants presented with fluentaphasia as a result of a left temporal-parietal lesion from ischaemic cerebrovascularaccident (J2, J4, and J5), closed head injury sustained from a fall (J3), or followingsurgical removal of a meningioma (J1). All participants were at least 1 year post-onsetexcept J3 (who was 7 months post brain injury at the time of initial testing) with noreported history of any other long-standing neurological conditions. They were nativespeakers of standard American English and had at least high school education. Allparticipants were pre-morbidly right-handed and had normal visual and hearing acu-ity. J1 reported minimal peripheral visual field deficits that did not significantly impacther everyday function. All relevant demographic and neurological information aboutthe participants are presented in Table 1.

Language testing

All the participants completed initial language evaluation (results summarised inTable 2). They were all diagnosed with fluent aphasia as per the Western Aphasia

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

512 SAMPSON AND FAROQI-SHAH

TABLE 1Participants’ profiles

Age/genderYears of

education Occupation Aetiology Time post-onset

J1 59/F 21 Budget director Left CVA 1 yearJ2 69/M 12 Stock investor Left CVA 3 yearsJ3 65/M 12 Construction

estimatorLeft TBI 7 months

J4 73/M 12 Line operator Left CVA 1 yearJ5 79/F 16 School

counselorLeft CVA 4 years

Battery (WAB; Kertesz, 1982) with a fluency score greater than or equal to five.Additionally, they all produced at least 9% of narrative speech as jargon errors dur-ing picture descriptions of the WAB and the Boston Diagnostic Aphasia Examination(BDAE; Goodglass, Kaplan, & Baressi, 2001). Every attempted production that wasa jargon error was counted as a single instance of jargon production (self-correctionsand word fragments were not individually counted as this would result in an artificiallyinflated jargon score). Any production in spontaneous speech that was a semanticallyand phonologically unrelated real-word error (e.g., climb for fork), phonologicallyrelated real-word error (e.g., cork for fork), or phonologically related and unre-lated non-word error (/ θOrk/ or /blaIn/ for fork) was identified as a jargon error.Participants varied in the quantity of jargon produced in narrative speech and in theextent to which targets and errors overlapped. Self-monitoring ability as evidenced byattempts at self-correction of errors produced in spontaneous speech (picture descrip-tion) varied among the participants (Table 2). Samples of spontaneous speech areprovided in Appendix A. Participants’ auditory processing proficiency was not partof the inclusionary criteria as this was a dependent measure. Additionally participantJ3’s cognitive skills were examined using the Test of Non-verbal Intelligence – Thirdedition (TONI-3; Brown, Sherbenou, & Johnsen, 1997) to establish the absence of anycognitive impairment secondary to TBI that may impact his performance (deviationquotient: 120; percentile rank: 91).

Stimuli

Line drawings of 120 nouns were selected from the International Picture NamingProject (IPNP) database (Szekely et al., 2004) as stimuli for picture naming, wordrepetition, and single-word identification. Stimuli were selected based on syllable com-plexity (monosyllabic/ multisyllabic [2–4-syllable] words) and lexical frequency (highfrequency: log frequency of > 2.5, low frequency: log frequency of < 2.0; lexical fre-quencies from CELEX; Baayen, Piepenbrock, & van Rijn, 1993). The pictures werepresented on 5 in. × 4 in. index cards for picture naming. The stimuli for the repeti-tion tasks were audio recorded by two native speakers of Standard American English(one male, one female) and presented via headphones.

Non-words were created from these 120 nouns by systematic alteration of their syl-lables. In monosyllabic and bisyllabic words either the initial phoneme/syllable or thefinal phoneme/syllable was substituted. In trisyllabic and four-syllable words, eitherthe initial two or the final two syllables were modified. Final voiceless phonemes of

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 513

TAB

LE2

Part

icip

ants

’lan

gu

age

pro

file

ob

tain

edfr

om

init

iall

ang

uag

ete

stin

gu

sin

gth

eW

este

rnA

ph

asia

Bat

tery

(WA

B;K

erte

sz,1

982)

Aph

asia

type

WA

BA

Qa

(max

=10

0)F

luen

cy(m

ax=

10)

Info

rmat

ion

cont

ent

(max

=10

)C

ompr

ehen

sion

(max

=10

)R

epet

itio

n(m

ax=

10)

Nam

ing

(max

=10

)T

otal

erro

rs(%

)Ja

rgon

b

(%)

Att

empt

edco

rrec

tion

sb

(%)

J1T

rans

cort

ical

sens

ory

45.8

5.0

3.0

4.6

9.0

1.3

3230

.59.

3

J2W

erni

cke’

s28

.66.

02.

04.

32.

00.

013

11.4

0.0

J3C

ondu

ctio

n64

.27.

03.

08.

66.

66.

911

.510

.24.

5J4

Ano

mia

80.4

9.0

7.0

9.2

8.5

6.5

109.

240

.0J5

Ano

mia

81.8

9.0

7.0

9.3

8.1

7.5

11.8

9.0

38.5

aW

este

rnA

phas

iaB

atte

ry(K

erte

sz,1

982)

;AQ

:Aph

asia

Quo

tien

t.bJa

rgon

and

atte

mpt

edse

lf-c

orre

ctio

nsof

thes

eer

rors

onna

rrat

ives

obta

ined

from

pict

ure

desc

ript

ion

task

sof

the

Wes

tern

Aph

asia

Bat

tery

(WA

B)

and

the

Bos

ton

Dia

gnos

tic

Aph

asia

Exa

min

atio

n(B

DA

E).

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

514 SAMPSON AND FAROQI-SHAH

altered syllables were converted to voiced phonemes, and final fricatives and affricateswere substituted by stop consonants. Alteration of the syllable structure includedboth consonant and vowel substitutions in multisyllabic words. None of the creatednon-words violated the phonotactic probabilities in English. All the created stimuli(including some modifications that resulted in extremely low frequency real words)were judged to be non-words in a lexical decision task by at least two (of three) adultspeakers of Standard American English on whom the stimuli were piloted. Thesenon-words were used for non-word repetition, auditory lexical decision, and speechdiscrimination tasks. The word and non-word stimuli are provided in Appendix B. Forthe noise-masked conditions of picture naming and word and non-word repetition,white noise was generated and presented via a computer at participants’ self-reportedmaximum tolerance level (between 70 and 85 dB SPL), using headphones.

The speech discrimination task utilised 120 word/non-word stimuli pairs (e.g., cug–cup or cug–cug or cup–cup). Of the targets, 50% were identical pairs and 50% weredissimilar pairs. The lexical decision task used 60 real words and 60 non-words (withequal representation of frequency and word length). The 120 nouns that were used forthe picture naming were used as both targets and distractors in single-word identifi-cation. In the single-word identification task the stimulus and three distractors (onesemantically related, one phonologically related, and one visually related to target)were presented together on 8 in. × 11 in. cards.

Procedure

All participants were tested individually and completed the experimental tasks oversix sessions of approximately 1 hour each, with appropriate rest breaks as needed.The instructions for all testing were provided verbally and in written form andwere repeated if necessary. The stimuli and tasks were identical for all participants,but within any task stimuli were presented in a pre-determined random sequence.The auditory processing tasks were randomly assigned to any three alternate test-ing sessions and the sequence of presentation of all tasks was counterbalanced acrossparticipants.

Speech production tasks

The three production tasks (picture naming, non-word repetition, and word repeti-tion) were administered under two listening conditions (normal auditory feedback andmasking noise). Depending on the task being performed, participants were instructedto provide a single-word naming or a single-word repetition response. They were alsodirected to correct their response if they recognised an error in their production. Aftereach verbal (naming/repetition) response the participants were asked to indicate ifthey thought that their final response was correct or incorrect by pointing to a check-mark or an X. During the non-word repetition task the participants were informedthat the stimuli were not real words in English.

The procedures were identical for the normal listening and masking noise condi-tions. Participants were exposed to any target only once during a session in order toavoid practice effects. All participants’ responses were recorded via a microphone on adigital voice recorder. Specific feedback about accuracy of performance was not pro-vided. Participants were provided with at least 10 practice trials for each task. Noneof the participants had any difficulty understanding the tasks after written/verbal

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 515

instructions and the practice trials. Response duration of 45 seconds was providedfor each trial.

Transcription and scoring. Participants’ verbal responses were recorded during thesessions and later transcribed using broad IPA transcription. Reliability of tran-scriptions and scoring was established on 30% of all responses for every participantby a second independent transcriber. Inter-transcriber agreement averaged at 96%across all participants. A third transcriber resolved any differences. The first completeresponse for each target was used for scoring and analysis. Jargon errors in picturenaming and word repetition were identified according to the operational definition(discussed under language testing). All inaccurate productions in non-word repetitionwere identified as jargon errors since semantic relatedness cannot be established giventhe nature of the target stimuli. Only accurate initial responses were scored as correct.Any other variant of the target word (semantic/phonological deviations, non-words,and no responses) as well as incorrect responses eventually self-corrected to the targetwere all coded as incorrect responses. The overall occurrence of jargon was calculatedfrom the incorrect responses as:

Jargon score (%)

= Number of responses produced as jargon × 100Total number of stimuli in the task − Number of no responses in production task

Therefore higher jargon scores reflected poorer accuracy in production.Participants’ final productions of the target (after self-corrections) were also scoredfor accuracy to determine the success of self-corrections. The accuracy with whichparticipants correctly recognized whether their production was correct or incorrectwas used to calculate a self-monitoring score for each task:

Monitoring score (%)

= Number of instances of correct self-judgement of accuracy × 100Total number of stimuli in the task − Number of no responses in self-judgement

Hence higher monitoring scores reflected better self-monitoring.

Auditory processing tasks

Auditory processing was assessed using speech discrimination, auditory lexical deci-sion, and single-word identification. None of the tasks required any verbal response.In the speech discrimination task participants were instructed to point to a checkmarkif the two stimuli they heard were the same, and to an X if they were different. In lexi-cal decision participants indicated if the word that they just heard was a real word ornot by pointing to a checkmark or an X. In the single-word identification task partici-pants had to match the auditorily presented stimulus to the target picture from a fieldof four.

Scoring. Participants’ responses to auditory processing tasks were noted duringthe testing sessions and scored for accuracy of performance. Further, the accuracy

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

516 SAMPSON AND FAROQI-SHAH

of single-word identification on each target was compared with the participant’sself-monitoring accuracy of that target on picture naming (under normal listeningcondition) on an item analysis to determine correspondence between comprehensionand self-monitoring for specific items.

RESULTS

Participants demonstrated a wide range of variability in jargon production duringsingle-word production across all the experimental tasks (Tables 3 and 4). The severityof jargon production in picture naming closely paralleled the proportion of jargon inspontaneous speech elicited during initial language testing (comparing percentages inTables 2 and 4). J1, who produced the most jargon in spontaneous speech, also had theleast accuracy in picture naming; and J5, who demonstrated the least deficits overall,also produced fewest errors in naming. Interestingly, performance on the word andnon-word repetition tasks was not clearly associated with narrative speech.

In general, all participants demonstrated most jargon errors in picture naming(range = 37.5–100%; M = 74.75%; SD = 26.5), followed by non-word repetition(range = 51.7–98.3%; M = 69.9%; SD = 16.0), and word repetition (range =11.7–81.7%; M = 34.5 %; SD = 24.1); all χ2(1, N = 120) > 13; p < .05 (Table 3).Participants generally produced more jargon under masking noise in word repetition(except J1 who performed better) and picture naming. Performance was more variablein non-word repetition: J2 produced less jargon while other participants demonstratedincreased jargon production under masking noise and J5 was impaired equally underboth listening conditions. Participants also varied in self-monitoring scores across thetasks ranging from 0% to 64.2% in picture naming (M = 27.5%; SD = .29), .8% to53.3% in non-word repetition (M = 31.5%; SD = .18), and 17.5% to 90% in word rep-etition (M = 67%; SD = .24) across all participants under both listening conditions,all χ2(1, N = 120) > 11; p < .05 (Table 3).

Jargon production and self-monitoring

Correlation analysis between participants’ jargon and self-monitoring scores (pooledacross listening conditions) revealed significant negative correlation in picture nam-ing (Spearman’s r = −.96, p < .01), word repetition (Spearman’s r = −.99, p <

.01), and non-word repetition (Spearman’s r = −.96, p < .01). Therefore, despitesome inter-individual variability, self-monitoring scores were significantly negativelycorrelated with jargon scores on all tasks. In the following sections the results are pre-sented according to the three factors that influence deficits in self-monitoring of speech(post-articulatory feedback, auditory processing, and task effects).

Feedback and self-monitoring

Participants’ self-monitoring scores on picture naming, non-word repetition, andword repetition were compared across the two listening conditions (with and with-out masking noise) to examine the contribution of the post-articulatory monitoringloop towards the success of self-monitoring. Every participant except J2 demon-strated poorer self-monitoring under masking noise on picture-naming and wordrepetition tasks (McNemar’s change test, p < .05; Table 3). J2 demonstrated a floorlevel of performance under both listening conditions (in terms of jargon production

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 517

TAB

LE3

Su

mm

ary

of

par

tici

pan

ts’e

rro

rd

etec

tio

nan

der

ror

corr

ecti

on

sp

erfo

rman

ceac

ross

task

s

Jarg

onsc

orea

Jarg

onde

tect

edb

Mon

itor

ing

scor

ecA

ttem

pted

self

-cor

rect

ions

dS

ucce

ssof

self

-cor

rect

ions

e

Nor

mal

Mas

king

Nor

mal

Mas

king

Nor

mal

Mas

king

Nor

mal

Mas

king

Nor

mal

Mas

king

n(%

)n

(%)

n(%

)n

(%)

n(%

)n

(%)

n(%

)n

(%)

n(%

)n

(%)

Pic

ture

nam

ing

J111

797

.5∗

120

100.

0∗0

0.0∗

00.

0∗5

4.2∗

00.

0†∗

105

87.5

∗10

184

.2∗

21.

90

0.0

J211

696

.7∗

117

97.5

∗0

0.0

00.

04

3.3∗

43.

3∗11

797

.5∗

120

100.

0∗0

0.0

00.

0J3

104

86.7

∗10

990

.8†∗

98.

6∗1

.825

20.8

∗12

10.0

†∗11

495

.0∗

9780

.8∗

21.

8∗0

0.0

J450

41.7

∗58

48.3

†∗3

6.0∗

35.

2∗74

61.7

∗68

56.7

†∗18

15.0

∗27

22.5

∗8

44.4

622

.2J5

4537

.5∗

6150

.8†∗

24.

4∗2

3.3∗

7764

.2∗

6150

.8†∗

1815

.0∗

2117

.5∗

527

.83

14.3

Non

-wor

dre

peti

tion

J183

69.2

6251

.732

38.6

3251

.858

48.3

6453

.3†

1.8

1.8

00.

01

100.

0J2

118

98.3

114

95.8

00.

00

0.0

21.

65

4.2

75.

80

0.0

00.

00

0.0

J383

69.2

9276

.7†

00.

00

0.0

3730

.81

.8†

00.

02

1.7

00.

01

50.0

J468

56.7

7058

.32

2.9

11.

452

43.3

5243

.35

4.2

43.

30

0.0

125

.0J5

7461

.774

61.7

961.

30

0.0

4739

.248

40.0

504.

22

1.7

00.

00

0.0

Wor

dre

peti

tion

J118

15.0

1411

.7†

00.

00

0.0

104

86.7

108

90.0

†1

.81

.80

0.0

110

0.0

J289

75.4

9881

.7†

00.

00

0.0

3025

.021

17.5

†24

20.0

86.

70

0.0

00.

0J3

2823

.331

25.8

00.

00

0.0

9276

.792

76.7

†1

.82

1.7

110

0.0

150

.0J4

2621

.739

32.5

†6

23.1

1025

.610

184

.281

67.5

†5

4.2

54.

22

40.0

120

.0J5

3226

.738

31.7

†7

21.9

1026

.394

78.3

8268

.3†

43.

35

4.2

250

.00

0.0

aA

mou

ntof

jarg

onpr

oduc

ed.

bA

mou

ntof

jarg

onde

tect

edac

cura

tely

onse

lf-j

udge

men

tof

resp

onse

s.c A

mou

ntof

jarg

onan

dco

rrec

tly

prod

uced

resp

onse

sde

tect

edac

cura

tely

onse

lf-j

udge

men

tof

resp

onse

s.dTo

tal

num

ber

ofre

spon

ses

(err

ored

and

corr

ect

resp

onse

s)th

atw

ere

spon

tane

ousl

yat

tem

pted

tobe

self

-co

rrec

ted.

e Num

ber

ofat

tem

pted

self

-cor

rect

ions

that

wer

esu

cces

sful

lyap

prox

imat

edto

targ

et.†

Diff

eren

ces

insc

ores

betw

een

liste

ning

cond

itio

nsar

est

atis

tica

llysi

gnifi

cant

onM

cNem

arch

ange

test

,p<

.05.

∗ Diff

eren

ces

insc

ores

amon

gth

eth

ree

prod

ucti

onta

sks

are

stat

isti

cally

sign

ifica

nton

chi-

squa

rete

st,p

<.0

5.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

518 SAMPSON AND FAROQI-SHAH

TABLE 4Accuracy

Speechdiscrimination

(%)

Auditorylexical decision

(%)

Single-wordIdentification

(%)

Monitoringscore picturenaming (%)

Monitoringscore non-wordrepetition (%)

Monitoringscore word

repetition (%)

J1 96.7∗ 65.8 57.5 4.2† 48.3† 86.7†

J2 88.3∗ 82.5 63.3 3.3† 1.6† 25.0†

J3 88.3∗ 75.8 84.2 20.8† 30.8† 76.7†

J4 97.5∗ 96.7 78.3 61.7† 43.3† 84.2†

J5 93.3 95.0 93.3 64.2† 39.2† 78.3†

Summary of participants’ accuracy of auditory processing in comparison to self-monitoring accuracyin single-word production (picture naming, non-word repetition and word repetition in normal listeningcondition).

∗Differences in accuracy scores between the three auditory processing tasks are statistically significanton the chi-square test, p < .05.

†Differences in accuracy scores between lexical decision task and self-monitoring during the productiontask are statistically significant on the chi-square test, p < .05.

and monitoring) providing little room for deterioration. Participants varied in theirperformance on non-word repetition under masking noise. J1 and J3 demonstratedpoorer self-monitoring—J1: χ2(1, N = 120) = 6.0, p < .05; J3: χ2(1, N = 120) =9.0, p < .05—while the other three participants demonstrated no significant change inself-monitoring non-word repetitions under masking noise (Table 3).

Therefore results indicate that in general, introduction of an auditory masker tolimit post-articulatory feedback resulted in more jargon and poorer self-monitoring,particularly in picture naming and word repetition. This suggests that participantsrely on post-articulatory feedback to self-monitor their productions. The impact ofmasking noise on self-monitoring non-word repetitions was more variable.

Auditory processing and self-monitoring

Table 4 summarises participants’ auditory processing proficiency in speech discrimi-nation, lexical decision, and single-word identification. All participants demonstratednear normal speech discrimination (range = 88–97.5%; M = 92.8%; SD = 4.4) andpoorer lexical decision (range: 65.8–95%; M = 83.2%; SD = 13.0). Single-word iden-tification was the most challenging input processing task for almost all participants(range = 57.5–93.3%; M = 75.3%; SD = 14.8) except J3 whose performance did notdiffer for lexical decision and single-word identification—75.8% versus 84.2%; χ2(1, N= 120) = 2.60, ns. Most participants demonstrated significant reduction in accuracyof auditory processing as the tasks included more components—J1: χ2(2, N = 120) =52.24, p < .05; J2: χ2(2, N = 120) = 23.97, p < .05; J3: χ2(2, N = 120) = 6.82, p <

.05; J4: χ2(2, N = 120) = 33.82, p < .05—except J5 whose auditory processing was atceiling level of performance, χ2(2, N = 120) = .39, ns.

Participants’ single-word identification and monitoring scores (in picture namingunder normal listening) were correlated in order to examine the relationship betweenauditory comprehension abilities and self-monitoring. Table 4 does not indicate a con-sistent pattern of relationship between single-word identification and self-monitoringability (for, e.g., participants J4 and J5 have identical monitoring scores but performdifferently in single-word identification tasks). The correlation coefficient between

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 519

Figure 2. Association between self-monitoring scores in picture naming (normal listening) and single-wordidentification scores on item analysis in each participant. The upper two stacks represent correspon-dence between performance in self-monitoring and single-word identification (number of stimuli thatwere monitored and identified correctly/incorrectly). The lower two stacks represent mismatches betweenself-monitoring and comprehension (number of stimuli where they were either correctly monitored andincorrectly identified or where they were incorrectly monitored but correctly identified on single-wordidentification).

single-word identification and self-monitoring, though high, was not statisticallysignificant (Spearman’s r = .80; ns).

An item-by-item comparison of success in single-word identification and self-monitoring of picture naming was performed and the findings are illustrated inFigure 2. The item analysis revealed that a majority of the stimuli that were correctlyidentified on the single-word identification were incorrectly monitored during namingor incorrectly identified and correctly monitored by participants J1, J2, and J3 (Figure2). Hence there was a greater mismatch than correspondence between performance onsingle-word identification and self-monitoring in these individuals (number of mis-matches versus matches in identification-monitoring are as follows: J1: 72 versus 48;J2: 74 versus 46; J3: 89 versus 31); Fisher exact test: all χ2(1, N = 120) > 9.5; p < .01.The reverse pattern was observed in J4 and J5 where their performance on single-wordidentification and self-monitoring in picture naming corresponded rather than differedon most stimuli (Figure 2; number of mismatches versus matches in identification-monitoring are as follows: J4: 28 versus 92; J5: 45 versus 75); Fisher exact test: allχ2(1, N = 120) > 15; p < .01. In other words, the item analysis indicated that theparticipants with a greater amount of jargon (J1, J2, and J3) demonstrated limitedassociation between performance on single-word comprehension and self-monitoringtasks, while participants who produced relatively less jargon (J4, J5) showed higherconsistency between items correctly identified and monitored.

Results therefore indicate that participants’ error monitoring in self-generatedspeech was poorly correlated with their single-word comprehension abilities, provid-ing poor support for a relationship between them. However, the two participants whowere least severe in their jargon (J4 and J5) demonstrated a closer correspondence inaccuracy of self-monitoring and comprehension on the item analysis.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

520 SAMPSON AND FAROQI-SHAH

Encoding demands (task complexity) and self-monitoring

A summary of participants’ ability to detect and correct speech errors is provided inTable 3. Participant J1 detected errors in non-word repetition only—normal listeningcondition: χ2(2, N = 120) = 61.0, p < .05; masking noise condition: χ2(2, N = 120)= 86.8, p < .05—and J3 detected errors only in picture naming—normal listeningcondition: χ2(2, N = 120) = 10.03, p < .05; masking noise condition: χ2(2, N = 120)= 1.96—–while failing to detect any errors on other tasks. The difference in errordetection accuracy on the production tasks in Participants J4 and J5 were statisticallysignificant under both listening conditions—J4: normal listening condition: χ2(2, N= 120) = 11.1, p < .05, masking noise condition: χ2(2, N = 120) = 20.31, p < .05; J5:normal listening condition: χ2(2, N = 120) = 15.71, p < .05, masking noise condition:χ2(2, N = 120) = 22.2, p < .05. J2 was the only participant who failed to detect anyof his errors on all production tasks under both listening conditions.

It is noteworthy that all participants reported that their responses were accurateon almost all their productions. For example, even though J2 produced about 97%of his responses as jargon, he detected none of his errors, and reported that all hisresponses were correct (Table 3). Signal detection analysis of self-judgement responsesconfirmed that all participants overestimated their production accuracy while self-monitoring their responses on all tasks despite adequate training in performing themonitoring task (D-prime scores: Picture naming: range: −4.26 to .68; M = −1.82;Non-word repetition: range: −4.26 to 2.23; M = −.22; Word repetition: range: −1.87to 3.1; M = 1.28). Hence participants’ performance on self-judgements further atteststo their self-monitoring failure.

Participants J1, J2, and J3 attempted to correct almost all their responses in pic-ture naming with limited success marked by few identifiable approximations to target.Only J2 demonstrated significantly more attempts at self-correction of errors on wordrepetition than non-word repetition in the normal listening, χ2(2, N = 120) = 10.7, p< .05, and masking noise condition, χ2(2, N = 120) = 6.34, p < .05. None of the otherparticipants differed in their attempts at error correction between the two repetitiontasks. All participants demonstrated very few attempts at self-correction of errors inthe repetition tasks and they were generally successful in approximating to target. J4and J5 produced fewer errors and thus had fewer opportunities to self-correct overall.Interestingly, even though J4 and J5 attempted limited self-corrections compared toothers in picture naming (15% each versus 87.5 to 97.5% for the others), they weremore successful at their attempts to approximate to target under normal listening andmasking noise conditions (Table 3).

In summary, very few errors were truly detected by all participants in all the exper-imental tasks, indicating a self-monitoring failure. All participants produced fewererrors, attempted more self-corrections, and were more successful at these attempts inthe repetition tasks than picture naming.

DISCUSSION

The primary purpose of this study was to examine if self-monitoring was related to jar-gon production in individuals with fluent aphasia. Several aspects of this relationshipwere examined: (1) the role of post-articulatory feedback, (2) the relation between self-monitoring and auditory processing abilities, and (3) the role of encoding demands(production task complexity) in the success of self-monitoring. Self-monitoring was

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 521

assessed in picture naming and non-word and word repetition (each under two lis-tening conditions: normal listening and masking noise). Auditory processing wasexamined in three hierarchically demanding tasks: auditory discrimination, lexicaldecision, and single-word identification. Findings from the five participants indi-cated that the severity of self-monitoring impairment is strongly negatively correlatedwith the amount of jargon produced in all production tasks in all participants. Thestudy further found that (i) exclusion of external auditory feedback resulted in poorerself-monitoring and increased jargon production in all tasks, (ii) there was no clearassociation between auditory processing deficits and self-monitoring score, and (iii)success of self-monitoring (error detection and correction) varied as a function of theproduction task demands.

Jargon production and self-monitoring

This study found a strong negative correlation between self-monitoring and jargonproduction, consistent with most other reports of jargon production in fluent apha-sia (e.g., Ellis et al., 1983; Hanlon & Edmonson, 1996; Kohn et al., 1996; Maher etal., 1994; Marshall et al., 1998; Nickels & Howard, 1995; Shuren et al., 1995; seeMarshall, 2006, for a review). Some contrasting evidence has also been previouslyreported (Moses et al., 2004; Robson et al., 1999). But it must be noted that the partic-ipant reported by Moses et al. (2004) demonstrated task-specific variation in successof self-monitoring (increase in jargon production with concomitant decrease in suc-cess of self-monitoring was observed in picture naming than repetition and reading),which was also observed in the current study. And the majority of errors of the partic-ipant reported by Robson et al. (1999) were “No responses” rather than jargon errorsas was in the current study. The participant was reported to be aware of her failure torespond by indicating “tip-of-the-tongue” state rather than true error detection anderror correction as was evaluated in the current study.

As discussed earlier, perception- and production-based accounts of self-monitoringsuggest that impairments in self-monitoring in FAJ could arise from impaired feed-back, breakdown in auditory comprehension, or phonological retrieval (during encod-ing) deficits or any combination of these deficits (Figure 1). Each of these prospects isdiscussed in the following sections.

External feedback and self-monitoring

When external auditory feedback was limited using masking noise, the amount ofjargon increased and self-monitoring deteriorated for all participants in picture nam-ing (except J2) and word repetition. Masking noise affected self-monitoring only intwo participants for non-word repetition. Participants were generally least affectedfrom lack of post-articulatory feedback in non-word repetition, possibly because ofthe lack of pre-existing mental representations against which the verbal productionscould be compared. That is, in a majority of the instances, masking noise resultedin poorer self-monitoring. However, there was some individual variability in this pat-tern and non-word repetition was least affected by masking noise. To the best of theauthors’ knowledge, the use of masking noise to alter external feedback during self-monitoring in individuals with FAJ is novel. The general pattern of deterioration ofself-monitoring with masking noise suggests that the participants were utilising post-articulatory feedback to some extent. However, given that self-monitoring score was

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

522 SAMPSON AND FAROQI-SHAH

not perfect even in the normal listening condition (Table 3), additional breakdown(s)in other process(es) that contribute to self-monitoring is likely. Interestingly, even inparticipant J2 who demonstrated a floor effect producing almost all responses as jar-gon with very poor monitoring skills, task-specific differences in performance werenoted, further suggesting a deficit in other aspects of linguistic processing.

It is interesting that jargon production also increases under masking noise. It is pos-sible that, under conditions of altered auditory feedback, it was not that more errorswere necessarily produced but that fewer errors were caught by the monitor priorto articulation. Currently, our knowledge of the distribution of labour between pre-and post-articulatory monitoring mechanisms and (the possibly differential) criteriaemployed by them is controversial and is speculative at best.

Auditory processing and self-monitoring

Most participants performed above chance in all three auditory tasks (except J2).For all participants, performance deteriorated with increasing task complexity, withauditory discrimination being the easiest, followed by lexical decision and single-word identification respectively (except J2 who was at chance with lexical decisionand word identification). Correlation measures between single-word identificationand self-monitoring were not statistically significant. This is consistent with the find-ings of Maher et al. (1994), Marshall et al. (1985), Marshall et al. (1998), Nickelsand Howard (1995), Schlenck et al., (1987), and Shuren et al. (1995), who foundno relationship between self-monitoring and auditory comprehension abilities. Giventhe small number of participants in the study, it may not be surprising that signifi-cant correlations were not obtained. But the item analysis provided further supportfor this relative independence of auditory processing and self-monitoring abilitiesbecause a majority of the participants correctly comprehended the words that theyincorrectly monitored during their own productions and vice versa. Furthermore, allparticipants demonstrated disproportionately poor error detection in their own pro-ductions despite above-chance ability to distinguish real words from non-words inthe lexical decision task. The findings of this study not only confirm the dissociationbetween auditory processing and self-monitoring reported in prior studies, but alsoadd further evidence in terms of the item analysis. It is noteworthy and relevant that,although these two measures are not directly associated, participants do benefit fromfeedback received from on-line auditory input to self-monitor (as evidenced by par-ticipants’ poorer productions under masking noise). Therefore relative intactness ofbasic auditory processing abilities was not sufficient for self-monitoring success.

Encoding demands (task complexity) and self-monitoring

In this study three different production tasks were used to examine the role of varyinglexical and phonological encoding demands on self-monitoring abilities. All partici-pants revealed below-chance ability to detect self-generated jargon errors and showeda tendency to judge their jargon as correctly produced (Table 3). All participantsalso produced fewer errors, and were more successful at self-corrections in repeti-tion compared to picture naming. Similar findings of higher success of error repairin repetition than naming have also been reported by Marshall et al. (1998) in fourindividuals with jargon and variable deficits in self-monitoring. As pointed out byMarshall and colleagues, the most straightforward interpretation of this task effect

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 523

is to assume impairments in semantically mediated lexical selection and/or post-semantic phonological retrieval. That is, the presentation of an auditory target forrepetition minimised the need for lexical selection and phonological retrieval, thusimproving both production accuracy and self-monitoring accuracy. This interpreta-tion is also supported from detailed qualitative and quantitative analyses of jargonproduced by the participants in the current study, which revealed that phonologicalrelatedness between error and target was significantly greater for repetition than forpicture naming (Sampson & Faroqi-Shah, 2009). Further, four out of five participants(with the exception of J2) failed to show any length effect or serial position effectin their productions. Both these measures are considered indicative of post-lexicalphonological encoding difficulty, including impaired short term storage “buffer”deficits (as opposed to lexical selection or phonological retrieval; Franklin, Buerk,& Howard, 2002). So the cumulative pattern of task effects—poorer accuracy andphonological relatedness with picture naming, and lack of post-lexical phonologicalencoding factors—strongly points to lexical selection and/or phonological retrievalimpairments. Such impairments are likely to activate an unrelated string of phonemes,which may continue through the end stages of phonological-phonetic encoding and bearticulated as jargon (Butterworth, 1979).

As mentioned earlier, self-monitoring is achieved by comparing the produced utter-ance with the target, and if the target is partially retrieved or not retrieved (as inpicture naming) then self-monitoring cannot be performed. This explains why self-monitoring scores also showed a task effect. This sample of individuals presented withrelatively intact real-word/non-word detection, as gleaned from their lexical decisionperformance. Hence poor self-monitoring may be attributed to the availability of anincorrect model against which to compare their production. In a repetition task themodel is made available by the examiner and hence self-monitoring success is better(although not perfect).

It is tricky to further delineate with certainty whether both lexical selectionand phonological retrieval, or only one of these processes is impaired. Marshallet al. (1996) suggested that semantically mediated lexical selection errors are morelikely to result in semantic jargon errors (e.g., fork for spoon) rather than theneologistic/unrelated jargon (glit for spoon). Our participants predominantly pro-duced neologistic errors rather than semantic jargon (approximately 59.8% versus2.7% of total productions; Sampson & Faroqi-Shah, 2009). Hence the error patternfavours problems with post-semantic retrieval of phonological information. Given thatsingle-word identification is assumed to tap the semantically mediated lexical selectionsystem (Kay, Lesser, & Coltheart, 1992) and that all participants performed abovechance on this task (see Table 4, chance level for a four-choice task is 25%), supportfor any semantically mediated selection deficit is weak.

Conclusions

The overall performance of the five participants with FAJ suggests that self-monitoring is significantly impaired in this group and these two symptoms are stronglynegatively correlated. Participants appear to utilise post-articulatory perceptual feed-back mechanisms to augment self-monitoring. Given that unimpaired speakers alsoutilise this auditory feedback during speech production, we can conclude that ourstudy found little evidence of an obvious impairment in the utilisation of post-articulatory feedback by this group of participants with aphasia. This conclusion

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

524 SAMPSON AND FAROQI-SHAH

is also consistent with the failure to find any association between auditory process-ing and self-monitoring. That is, although auditory feedback is obviously requiredfor post-articulatory self-monitoring, this group of participants with jargon revealedthat the intactness (and deficits) in auditory processing subcomponents (discrimi-nation, lexical decision, and word identification) is not a sufficient explanation forself-monitoring deficits. Rather, self-monitoring deficit in these individuals appearsto be a consequence of the same production-specific encoding processes that resultin jargon production: particularly post-semantic retrieval of phonological informa-tion. The primary argument is that impaired lexical selection/phonological retrievalnot only provides inadequate input for post-lexical phonological encoding, but alsoan inadequate model for comparing intended with produced utterances. Evidence forthis comes from task-related variations in the severity and quality of jargon productionand parallel deterioration of self-monitoring. Post-semantic retrieval of phonologicalcode could be either affected by low level of activation of lexical entries, weakenedlinks between semantic and phonological codes, or overactivation/disinhibition ofmultiple lexical entries. Further research is needed to tease apart these explanations.

Limitations of the study

The generalisability of the conclusions drawn about self-monitoring in aphasic jargonare limited by the small sample size of this study, even though this sample is largerthan most prior studies (e.g., Hanlon & Edmonson, 1996; Kohn et al., 1996; Maher etal, 1994; Marshall et al., 1996, 1998; Robson et al., 1998). The generalisability is alsolimited by the participant characteristics to those with relatively less-severe auditoryprocessing deficits and those who produce modest amounts of jargon that containsprimarily phonologically related and unrelated real-word and non-word errors. Theamount of jargon produced by patients described in previous studies was not explicitlyquantified, and hence it is unclear how our participants compare to those in previousstudies. The method by which non-word stimuli were created may also impose method-ological limitations on the interpretation of the data because the procedure resulted insome stimuli that were real words, albeit of extremely low frequency.

Manuscript received 11 December 2009Manuscript accepted 2 September 2010

First published online 29 November 2010

REFERENCESBaayen, R. H., Piepenbrock, R., & van Rijn, H. (1993). The CELEX Lexical Database (Release 1) [CD-

ROM]. Philadelphia: Linguistic Data Consortium, University of Pennsylvania.Blackmer, E. R., & Mitton, J. L. (1991). Theories of monitoring and the timing of repairs in spontaneous

speech. Cognition, 39, 173–194.Brown, L., Sherbenou, R. J., & Johnsen, S. K. (1997). TONI-3: Test of Nonverbal Intelligence (3rd ed.).

Austin, TX: Pro-Ed.Butterworth, B. (1979). Hesitation and the production of verbal paraphasias and neologisms in jargon

aphasia. Brain and Language, 8, 133–161.Butterworth, B. (1985). Jargon aphasia: Processes and strategies. In S. Newman & R. Epstein (Eds.), Current

perspectives in dysphasia. Edinburgh, UK: Churchill Livingstone.De Smedt, K., & Kempen, G. (1987). Incremental sentence production, self-correction, and coordination.

In G. Kempen (Ed.), Natural language generation: Recent advances in artificial intelligence, psychology,and linguistics. Dordrecht, The Netherlands: Kluwer.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 525

Ellis, A., Miller, D., & Sin, G. (1983). Wernicke’s aphasia and normal language processing: A case study incognitive neuropsychology. Cognition, 15, 110–145.

Franklin, S., Buerk, F., & Howard, D. (2002) Generalised improvement in speech production for aparticipant with reproduction conduction aphasia. Aphasiology, 16, 1087–1114.

Goodglass, H., Kaplan, E., & Barresi, B. (2001). The Boston Diagnostic Aphasia Examination (BDAE) (3rded.). Baltimore: Lippincott Williams & Wilkins.

Hanlon, R. E., & Edmondson, J. (1996). Disconnected phonology: A linguistic analysis of phonemic jargonaphasia. Brain and Language, 55, 199–212.

Hartsuiker R. J., Bastiaanse, R., Postma, A., & Wijnen, F. (Eds.). (2005). Phonological encoding andmonitoring in normal and pathological speech. Hove, UK: Psychology Press.

Hartsuiker, R. J., & Kolk, H. H. J. (2001). Error monitoring in speech production: A computational test ofthe perceptual loop theory. Cognitive Psychology, 42, 113–157.

Hartsuiker, R. J., Kolk, H. H. J., & Martensen, H. (2005). The division of labor between internal and exter-nal speech monitoring. In R. J. Hartsuiker, R. Bastiaanse, A. Postma, & F. Wijnen (Eds.), Phonologicalencoding and monitoring in normal and pathological speech (pp. 187–205). Hove, UK: Psychology Press.

Hillis, A., Boatman, D., Hart, J., & Gordon, B. (1999). Making sense out of jargon: A neurolinguistic andcomputational account of jargon aphasia. Neurology, 53, 1813–1824.

Kay, J., Lesser, R., & Coltheart, M. (1992). PALPA: Psycholinguistic Assessments of Language Processingin Aphasia. Hove, UK: Lawrence Erlbaum Associates Ltd.

Kertesz, A. (1982). Western Aphasia Battery. Orlando, FL: Grune & Stratton.Kohn, S. E., Smith, K. L., & Alexander, M. P. (1996). Differential recovery from impairment to

phonological lexicon. Brain and Language, 52, 129–149.Kolk, H. H. J. (1995). A time-based approach to agrammatic production. Brain and Language, 50, 282–303.Laver, J. D. M. (1973). The detection and correction of slips of tongue. In V. A. Fromkin (Ed.), Speech

errors as linguistic evidence. The Hague, The Netherlands: Mouton.Laver, J. D. M. (1980). Monitoring systems in the neurolinguistic control of speech production. In V.

A. Fromkin (Ed.), Errors in linguistic performance, slips of the tongue, ear, pen and hand. New York:Academic Press.

Lazar, R., Marshall, R., Prell, G., & Pile-Spellman, J. (2000). The experience of Wernicke’s aphasia.Neurology, 55, 1222–1224.

Levelt, W. (1983). Monitoring and self-repair in speech. Cognition, 14, 41–104.Levelt, W. (1989). Speaking: From intention to articulation. Cambridge, MA: MIT Press.Maher, L., Gonzalez-Rothi, L., & Heilman, K. (1994). Lack of error awareness in an aphasic patient with

relatively preserved auditory comprehension. Brain and Language, 46, 402–418.Maneta, N., Marshall. J., & Lindsay, J. (2001). Direct and indirect therapy for word sound deafness in

aphasia. The International Journal of Language and Communication Disorders, 36(1), 91–106.Marshall, J. (2006). Jargon aphasia: What have we learned? Aphasiology, 20, 387–410.Marshall, J., Pring, T., Chiat, S., & Robson, J. (1996). Calling a salad a federation: An investigation of

semantic jargon. Paper 1, Nouns. Journal of Neurolinguistics, 9, 237–250.Marshall, R., Neuberger, S., & Phillips, D. (1994). Verbal self-correction and improvement in treated

aphasic clients. Aphasiology, 8, 535–547.Marshall, R., Rappaport, B., & Garcia-Bunuel, L. (1985). Self-monitoring behaviour in a case of severe

auditory agnosia with aphasia. Brain and Language, 24, 297–313.Marshall, J., Robson, J., Pring, T., & Chiat, S. (1998). Why does monitoring fail in jargon aphasia?

Comprehension, judgement, and therapy evidence. Brain and Language, 63, 79–109.Moses, M., Nickels, L., & Sheard, C. (2004) Disentangling the web: Neologistic perseverative errors in

jargon aphasia. Neurocase, 10, 452–461.Nickels, L., & Howard, D. (1995). Phonological errors in aphasic naming: Comprehension, monitoring and

lexicality. Cortex, 31, 209–237.Oomen, C. C. E., & Postma, A. (2001). Effects of time pressure on mechanisms of speech production and

self-monitoring. Journal of Psycholinguistic Research, 30, 163–184.Oomen, C. C. E., Postma, A., & Kolk, H. H. J. (2001). Prearticulatory and postarticulatory self-monitoring

in Broca’s aphasia. Cortex, 37, 627–641.Peuser, G., & Temp, K. (1981). The evolution of jargon aphasia. In J. Brown (Ed.), Jargon aphasia. New

York: Academic Press.Postma, A. (2000). Detection of errors during speech production: A review of speech monitoring models.

Cognition, 77, 97–131.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

526 SAMPSON AND FAROQI-SHAH

Postma, A., & Kolk, H. H. J. (1993). The covert repair hypothesis: Prearticulatory repair processes in normaland stuttered dysfluencies. Journal of Speech and Hearing Research, 36, 472–487.

Postma, A., & Oomen, C. E. (2005). Critical issues in speech monitoring. In R. Hartsuiker, Y. Bastiaanse,A. Postma, & F. Wijnen (Eds.), Phonological encoding and monitoring in normal and pathological speech(pp. 157–166). Hove, UK: Psychology Press.

Robson, J., Marshall, J., Pring, T., & Chiat, S. (1999). Phonological naming therapy in jargon aphasia:Positive but paradoxical effects. The Journal of International Neuropsychological Society, 4, 675–686.

Robson, J., Pring, T., Marshall, J., & Chiat, S. (2003). Phoneme frequency effects in jargon aphasia: Aphonological investigation of neologisms. Brain and Language, 85, 109–124.

Roelofs, A. (2005). Spoken word planning, comprehending, and self-monitoring: Evaluation ofWEAVER++. In R. J. Hartsuiker, R. Bastiaanse, A. Postma, & F. Wijnen (Eds.), Phonological encodingand monitoring in normal and pathological speech (pp. 42–63). Hove, UK: Psychology Press.

Sampson, M. & Faroqi-Shah, Y. (2009, October). Tomato to baritood: The source of non-words in jargonaphasia. Poster session – Academy of Aphasia, Boston, MA. Retrieved from http://www.bsos.umd.edu/hesp/facultyStaff/shahy/AOA_2009_Jargon_Poster.pdf

Schiller, N. O. (2005). Verbal self-monitoring. In A. Culter (Ed.), Twenty-first century psycholinguistics: Fourcornerstones. Hillsdale, NJ: Lawrence Erlbaum Associates Inc.

Schlenk, K. J., Huber, W., & Willmes, K. (1987). “Prepairs” and repairs: Different monitoring functions inaphasic language production. Brain and Language, 30, 226–244.

Shuren, J., Smith Hammond, C., Maher, L., Rothi, L., & Heilman, K. (1995). Attention and anosognosia:The case of a jargon aphasic patient with unawareness of language deficit. Neurology, 45, 376–378.

Szekely, A., Jacobsen, T., D’Amico, S., Devescovi, A., Andonova, E., Herron, D., et al. (2004). A new onlineresource for psycholinguistic studies. Journal of Memory and Language, 51, 247–250.

Van Wijk, C., & Kempen, G. (1987). A dual system for producing self-repairs in spontaneous speech:Evidence from experimentally elicited corrections. Cognitive Psychology, 19, 403–440.

Wheeldon, L. R., & Levelt, W J. M. (1995). Monitoring the time-course of phonological encoding. Journalof Memory and Language, 34, 311–334.

APPENDIX A

Sample narratives of the Western Aphasia Battery picture description task (WAB;Kertesz, 1982)

Patient J1

There’s a blee..a tall blee..bee. . .tee. . .that’s not right. A tall tee. . .she is glopping.Mind thrifting. . .a blaket. . .blurring. That’s aflig. . .a flig. . .windy day. This water. ..caves. . .waves. . .he grating cheeps across ling fleam. That’s a glader. There’s food inthere. . .maybe a picnnet? I don’t know. . .nice house! The logweed door is not pretty.. .u know what I mean.

Patient J2

Two girls house and the girl. . .alright. . .they are eating like this. . .this boy’s eating likethat. . .they are eating like that. . .alright. . .light and the dogs like that. . .house is likethat right. . .he is just outside today..he is outside. . .the dog is like that outside. . .it’sfirst like that. . .it’s a small thing like that. . .I say like that but my pace is all glistening.

Patient J3

It’s not a large house. it’s small. unless an awful lot of it goes back behind the house.they are whiking what they are doing in the front part which must be peeving. . .

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

SELF-MONITORING IN FLUENT APHASIA 527

leeling. . . weeding. . .there is a nicoverit spotole for the changer of the sep. . .uh. . .sec. . .uh. . . hanson. . .whatever it is.

Patient J4

This tree. . .no not tree. . .I can’t think of the word. . .this is under the tree. Theyare sitting on it. . .and this thing. . .the baket. . .the baket. . .the backet is on theblank. . .um. . .blanket. Yes, that’s the word. Wow! That was hard. They have a littleradio here on the blanket. There’s a dog. He’s looking at them.

Patient J5

It’s a nice bay. . .day. . .nice bay for a picnic. The family. . .mother. . .father. ..children..son. They have a big house with a nice lawn. . .the pool. . .no ocean. ..sea. . .that’s a chip. . .no ship. . .boat. . .a sail boad. Looks like it anyway. Do theyhave a dog? This wood here, this plank. . .you know what I mean. . .used to jump offit into the water. Oh my! Looks like a picnic. . .someone’s pishing there.

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011

528 SAMPSON AND FAROQI-SHAHA

PP

EN

DIX

BLi

sto

fst

imu

li

Rea

lWor

dN

on-w

ord

Rea

lWor

dN

on-w

ord

Rea

lWor

dN

on-w

ord

Acc

ordi

on/@’

kOrd

i@n/

/ε’p

εld

i@n/

Blim

p/bl

Imp/

/kl

Imp/

Cat

/kæ

t//kæ

g/A

irpl

ane

/’æ

rple

In/

/’æ

rklo

m/

Boa

t/bo

t//bo

b/C

hain

/t∫

eIn/

/de

In/

Alli

gato

r/’æ

lIgeI

t@r/

/’æ

lIpεt@

l/B

omb

/b6

m/

/b6

d/C

hair

/t∫

ær/

/t∫

Al/

App

le/’æ

p@l/

/’o

Ip@l

/B

owl/

bol/

/no

l/C

herr

y/’t∫

εri/

/’d

εri/

Arr

ow/’æ

ro/

/’o

ro/

Bri

de/br

aId/

/br

aIk/

Chi

cken

/’t∫

Ik@n

//’t∫

Ibεp/

Bac

kpac

k/’b

ækp

æk/

/’b

ækt

p/B

room

/br

um/

/br

ul/

Cla

mp

/kl

æm

p//pl

æm

p/B

allo

on/b@

’lun/

/ti

’run

/B

rush

/br

�∫/

/br

�m

/C

low

n/kl

an/

/kl

ak/

Ban

daid

/’b

ænd

e Id/

/’k

uNde

Id/

Cak

e/ke

Ik/

/ke

Ib/

Com

b/ko

m/

/to

m/

Bic

ycle

/’b

a IsI

k@l/

/’k

aIfo

k@l/

Can

dle

/’k

ænd

@l/

/’k

ænb

ut/

Cro

wn

/kr

an/

/kr

ap/

Bir

d/b Ä

d//gÄ

d/C

arro

t/’k

ær@

t//’k

ælu

p/C

up/k�

p//k�

g/D

esk

/dε

sk/

/dε

zd/

Fea

ther

/’fεð@r

//’fεsi

t/H

oof/hu

f//hu

b/D

octo

r/’d

6kt@

r//’p

ubtÄ

/F

inge

r/’fIN

@r/

/’fIm

Ik/

Hor

se/hO

rs/

/sO

rs/

Dog

/d 6

g//d6

p/F

lute

/flu

t//sl

ut/

Hos

e/ho

z//ho

k/D

onke

y/’d

6Nki

//’p

imki

/F

oot/f

t//∫

t/Ic

ecre

amco

ne/’a

Iskr

imko

n//’A

Ispu

ntAI

m/

Dri

ll/dr

Il//dr

Ä/

Gui

tar/gI

’tAr/

/du

’tAr/

Jack

et/’d

ækI

t//’d

æpe

Ig/

Duc

k/d�

k//k�

k/H

ange

r/’h

æN@

r//’h

æNu

t/Ju

mpr

ope

/’d

�m

prop

//’d

�m

plk/

Dus

tpan

/’d�

stpæ

n//’d

�st

il/H

arp

/h A

rp/

/lA

rp/

Kin

g/kI

N//tIN

/

Egg

/εg/

/εp/

Hat

/hæ

t//hæ

p/K

ite

/ka

It//ka

Ig/

Ele

phan

t/’ε

l @f@

nt/

/’ε

losε

kt/

Hea

rt/hA

rt/

/sA

rt/

Lem

on/’lε

m@n

//’lε

nil/

Env

elop

e/’ε

nv@l

op/

/’ju

m@r

op/

Hel

icop

ter/’h

εlIk

6pt@

r//’h

εlIp

ikεl/

Lip

s/lIp

s//jIp

s/E

ye/a I

//OI

/H

elm

et/’h

εlm

It//’h

εln

ug/

Lip

stic

k/’lI

pstIk

//’w

otst

Ik/

Mic

roph

one

/’m

aIkr

@fon

//’p

Ast@

fon/

Pic

ture

/’p

Ikt∫

Ä/

/’k

upt∫

Ä/

Roo

f/ru

f//ru

p/M

op/m

6p/

/n6

p/P

ig/pI

g//m

Ig/

Safe

/sæ

f//sæ

b/M

ushr

oom

/m�∫

rum

//’lo

frum

/P

inec

one

/’p

aInk

on/

/’p

aInt

il/Sa

ilor/’se

IlÄ/

/’f

uwÄ

/

Nai

l/ne

Il//ne

Ib/

Pir

ate

/’p

aIr@

t//’ti

r@t/

Saw

/sA

//fA

/

Pap

er/’p

e Ip@

r//’p

eIgu

l/Po

psic

le/’p

6psI

k@l/

/’p

6pf

tÄ/

Saxo

phon

e/’sæ

ks@f

on/

/’sæ

ksaI

hON/

Paw

/pO

//tO

/Po

tato

/p@

’teIto

//ti

’kut

o/Sh

irt/∫Ä

t//vÄ

t/P

each

/pi

t∫/

/ki

t∫/

Pyr

amid

/’p

Ir@m

Id/

/’t

w�m

Id/

Skis

/sk

iz/

/sk

ud/

Pea

r/pæ

r//gæ

r/R

adio

/’r

ædi

o//’r

æpi

ju/

Sled

/slεd/

/slεn/

Pea

s/pi

z//pi

m/

Rak

e/re

Ik/

/re

Im/

Sock

/s6

k//h6

k/P

en/pε

n//nε

n/R

ing

/rI

N//lIN

/Sp

atul

a/’sp

æt∫

εla

//’fl

Akεla

/

Pia

no/pi

’æno

//pi

’ula

/R

ocke

t/’r6k

εt/

/’lu

pεt/

Spid

er/’sp

aIdÄ

//’k

lidÄ

/

Stee

ring

whe

el/’st

I@rI

Nwil

//’k

lulε

mw

il/T

eeth

/tiθ/

/pi

θ/

Vas

e/

ves/

/ve

b/St

raw

berr

y/’st

r Obε

ri/

/’st

rOkI

lo/

Tel

epho

ne/’tε

l@fo

n//’k

urAf

on/

Ves

t/vε

st/

/vε

kt/

Swan

/sw

An/

/sw

Al/

Tel

esco

pe/’tε

l@sk

op/

/’tε

lvkl

aId/

Wai

ter/’w

eItÄ

//’rOI

gÄ/

Swea

ter/’sw

εt Ä

//’k

lutÄ

/T

iger

/’ta

IgÄ

//’g

igÄ

/W

heel

barr

ow/

‘wilb

æro

//’w

iltur

εl/

Tab

le/’te

Ib@l

//’te

IgÄ

/To

mat

o/to

’meI

to/

/to

’liku

/W

hip

/w

Ip/

/w

Id/

Tai

l/te

Il//kε

Il/T

urke

y/’t3

rki/

/’k

upki

/W

ig/w

Ig/

/lIg

/

Tea

r/t IÄ

//kI

Ä/

Um

brel

la/�

m’b

rεl@

//εl’k

lul@

/W

oman

/’w

m@n

//’w

læN/

Tee

pee

/’ti

pi/

/’ti

ka/

Uni

corn

/’ju

n IkO

rn/

/’ε

lIkOr

n/W

ood

/w

d//j

d/

Downloaded By: [Faroqi-Shah, Yasmeen] At: 13:22 28 February 2011