Identification of voices in disguised speech Jessica Clark* & Paul Foulkes** * University of York ** University of York & JP French Associates [email protected]

Identification of voices in disguised speech

Jessica Clark* & Paul Foulkes**

* University of York

** University of York & JP French Associates

[email protected]

IAFPA, Göteborg 2006

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0.1 outline

• experiment to test ability of lay listeners to identify disguised familiar voices

• voices have been disguised artificially, as with commercially available voice changers– pitch modified

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0.2 structure

1. introduction– rationale for experiment

2. experimental design– speakers– listeners– Control condition– Experimental conditions

3. results

4. discussion & conclusion

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1. Introduction

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1. Introduction

• technical speaker identification is the most frequent task for the forensic phonetician

• lay identification is also common in legal cases

• many previous studies have thus examined lay listeners’ ability to identify voices and the factors which affect their ability

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1.1 previous studies

• identification is not automatic or flawless

• listeners can make errors even with highly familiar voices – Ladefoged did not recognise his mother from a short

sample (Ladefoged & Ladefoged 1980)

– flatmates scored only 68% with 10 second samples (Foulkes & Barron 2000)

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1.1 previous studies

• identification may be affected by [Bull & Clifford 1984]

– type of exposure (active/passive)– length of sample– nature of sample (phone, direct, shouting etc)– delay between exposure and test– age of listener– hearing ability– sightedness– natural variability across individual listeners– specific features of voice– degree of familiarity– nature and extent of any disguise

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1.2 degree of familiarity

• all things equal, more familiar voices are easier to identify

• e.g. Hollien, Majewski & Doherty (1982)– listening tests with 10 male voices

listener group N % correct

(normal condition)

familiar 10 98

trained 47 40

unfamiliar 14 27

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1.3 disguise

• all things equal, disguised voices are harder to identify

• e.g. Hollien, Majewski & Doherty (1982)– various forms of disguise used

listener group N % correct (normal)

% correct (disguised)

familiar 10 98 79

trained 47 40 21

unfamiliar 14 27 18

machine approach (LTAS) 30

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1.3 disguise

• previous studies have examined various types of disguise– whisper, pencils between teeth, hypernasality,

dialect change, rate change, professional mimics

• but little if any work on voice changers– hardware based– software based– easily available

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www.maplin.co.uk

www.crimebusters911.com

www.blazeaudio.com

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1.3 disguise

• in our study we chose not to use real voice changers, in favour of total control over effects

• pitch shift chosen as a universal function

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2. Experimental design

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2.1 design outline

• simple design

• listeners asked to identify samples of familiar voices

• Control condition unmodified stimuli

• 4 Experimental conditions modified stimuli

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2.1 design outline

• degree of familiarity known to affect rate of successful identification

• thus we trained listeners to identify a group of speakers– controls degree of familiarity– all listeners had exactly the same exposure in terms

of length & quality of samples– identification task carried out under same conditions

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2.2 speakers

• 4 male speakers– 16-18 years old

• taken from IViE corpus (Grabe, Post & Nolan 2001)

– Leeds dialect (nearest to York)– reading text of Cinderella story

IViE speaker Experimental name

JP Edward

JW Matthew

MD Harry

RP David

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2.2 speakers

• training materials created for each speaker– c. 90 seconds of Cinderella (302 words)– edited out disfluencies, non-speech sounds, long

pauses– samples normalised for amplitude with Audacity

1.2.5

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2.3 listeners

• 36 listeners• variety of regional/social backgrounds• York residents• age range 19-55• 10 male, 26 female

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2.4 Control condition

• all 36 listeners – 4 voices * 90 seconds = c. 6 minutes

– presented by PowerPoint with speakers’ names

– Toshiba laptop– Aiwa A170 headphones– individually in quiet room

1. training phase

2. break

3. listening test

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• all 36 listeners

– 10 minutes

1. training phase

2. break

3. listening test


• all 36 listeners

– 8 stimuli (2 per

speaker)– duration c. 10 seconds– 5 second gap between– extracts from other parts

of Cinderella story– normalised for amplitude

with Audacity 1.2.5– answer sheet with names

1. training phase

2. break

3. listening test

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2.5 Experimental conditions

• 4 Experimental conditions

• listening tests same format as Control condition

• but stimuli modified for pitch

• Sound Forge 8.0– pitch shift effect– accuracy setting ‘high’– speech 1 mode– preserved durations

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(i) +8 semitones

(ii) +4 semitones

(iii) -4 semitones

(iv) -8 semitones

pitch shift > 8 semitones unnatural and partly incomprehensible

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listener group N conditions (semitones)

A 18 -8, +4

B 18 -4, +8

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• listening test 16-92 days after Control test– no clear effects for length of delay

• same training as in Control condition• 10 minute break• 2 stimuli for familiarisation

• 8 experimental stimuli per condition– consecutive runs for + and - stimuli

– order reversed for half of each group, but no effect

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3. Results

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• average correct identification = 4.8/8 (60%)

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Minus 8 Minus 4 Control Plus 4 Plus 8

ave

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• individuals’ range 8 to 0• 29/36 performed better than chance

control

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listeners

N c

orr

ect

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• ** sig. lower than in Control (p < .005, Wilcoxon)

• trend (n.s.) for higher scores in + conditions

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ave

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** ******

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-8 semitones

0

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listeners

N c

orr

ect

+8 semitones

0

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listeners

N c

orr

ect

+4 semitones

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listeners

N c

orr

ect

-4 semitones

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listeners

N c

orr

ect

• variability in listener performance, esp. ±4• majority perform above chance except -8

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3.3 variation by listener sex

• women sig. better in Control (p = .008, Mann-Whitney)

– trend (n.s.) maintained in Experimental tests– same pattern reported by Bull & Clifford (1984)

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N c

orr

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t

Male Female

**

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3.4 summary

• as predicted, identification rates were lower with disguised voices– lowest scores with most extreme form of disguise

(±8 semitones)

• identification rates slightly better when pitch shifted up than down

• trend for women to perform better than men

• variability across listeners

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4. Discussion & conclusion

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• tests reported here were not forensically realistic

• results may be affected by e.g.– degree of familiarity with voice– content of sample (vocabulary, syntax etc)– conditions of exposure (stress etc)– specific form of artificial disguise

• software, hardware system• combination of effects

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• considerable variation in listeners’ scores– courts should not assume all witnesses are equally

good at such tasks– supports broader principle that lay witnesses should

be tested in their ability to identify a voice

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• but even marked disguise was not catastrophic for listeners

• a broadly positive conclusion for lay speaker identification– a reasonable chance of identifying familiar voices

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• but a less positive conclusion respect to use of voice changers as a means of protecting vulnerable witnesses giving evidence

• more extreme forms of modification may affect intelligibility & naturalness

• less extreme forms of modification may render witness’s voice recognisable

• different modifications for different voices?

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• as ever…

• more work is needed

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thanks

tack

thanks to Peter French, Phil Harrison, Robin How

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References

Bull, R. & Clifford, B. (1984) Earwitness voice recognition accuracy. In G. Wells & E. Loftus (eds.) Eyewitness Testimony: Psychological Perspectives. Cambridge: CUP. pp. 92-123.

Foulkes, P. & Barron, A. (2000) Telephone speaker recognition amongst members of a close social network. Forensic Linguistics 7: 181-198.

Grabe, E., Post, B. & Nolan, F. (2001) English intonation in the British Isles: the IViE corpus. Final report to UK ESRC R000 237145. www.phon.ox.ac.uk/IViE

Hollien, H., Majewski, W. & Doherty, E. (1982) Perceptual identification of voices under normal, stress and disguise speaking conditions. Journal of Phonetics 10: 139-148.

Ladefoged, P. & Ladefoged, J. (1980) The ability of listeners to identify voices. UCLA Working Papers in Phonetics 49: 43-51.

Documents

Identification of voices in disguised speech Jessica Clark* & Paul Foulkes** * University of York ** University of York & JP French Associates [email protected]