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74.406 Natural Language Processing
Christel Kemke
Department of Computer Science
University of Manitoba
74.406 Natural Language Processing, 1st term 2004/5
Evolution of Human Language
• communication for "work"
• social interaction
• basis of cognition and thinking
(Whorff & Saphir)
Communication
"Communication is the intentional exchange of information brought about by the production and perception of signs drawn from a shared system of conventional signs."
[Russell & Norvig, p.651]
Natural Language - General
Natural Language is characterized by a common or shared set of signs
alphabeth; lexicon a systematic procedure to produce
combinations of signs syntax
a shared meaning of signs and combinations of signs (constructive) semantics
Natural Language Processing Overview
• Speech Recognition
• Natural Language Processing
• Syntax
• Semantics
• Pragmatics
• Spoken Language
Natural Language and Speech
Speech Recognition acoustic signal as input conversion into phonemes and written words
Natural Language Processing written text as input; sentences (or 'utterances') syntactic analysis: parsing; grammar semantic analysis: "meaning", semantic representation pragmatics: dialogue; discourse; metaphors
Spoken Language Processing transcribed utterances Phenomena of spontaneous speech
MorphologyA morphological analyzer determines (at least) the stem + ending of a word, and usually delivers related information, like the word class, the number and the person of the word. The morphology can be part of the lexicon or implemented as a single component, for example as a rule-based system.
eats eat + s verb, singular, 3rd pers
dog dog noun, singular
LexiconThe Lexicon contains information on words, as inflected forms (e.g. goes, eats) or word-stems (e.g. go, eat).
The Lexicon usually assigns a syntactic category, the word class or Part-of-Speech category
Sometimes also further syntactic information (see Morphology); semantic information (e.g. semantic classifications like ‘agent’); syntactic-semantic information, e.g. on verb complements like ‘give’ requires a direct object.
Lexicon
Example contents:
eats verb; singular, 3rd person;
can have direct object
dog dog, noun, singular; animal
semantic annotation
POS (Part-of-Speech) Tagging
POS Tagging determines word class or ‘part-of-speech’ category (basic syntactic categories) of single words or word-stems.
The det (determiner)
dog noun
eat, eats verb (3rd singular)
the det
bone noun
MorphologicalAnalyzer
Lexicon
Part-of-Speech(POS)
Tagging
GrammarRules
Parser
NLP - Syntactic Analysis
eat + s eat – verb Verb VP → Verb Noun VP recognized
3rd sing VP
Verb Noun
parse tree
Language and Grammar
Natural Language described as Formal Language L using a Formal Grammar G:
• start-symbol S ≡ sentence• non-terminals NT ≡ syntactic constituents• terminals T ≡ lexical entries/ words• production rules P ≡ grammar rules
Generate sentences or recognize sentences (Parsing) of the language L through the application of grammar rules from G.
Overgeneration / undergeneration: accept/generate sentences not in L / not all sentences from L.
Grammar
• Terminals can be words, part-of-speech categories, or more complex lexical items (including additional syntactic/semantic information related to the word).– dog– noun– dog: noun, singular; animal
• Non-Terminals represent (higher level) ‘syntactic categories’.– noun– NP (noun phrase)– S (sentence)
Grammar
Most often we deal with Context-free Grammars, with a distinguished Start-symbol S (sentence).
det the
noun dog | bone
verb eat | eats
NP det noun (NP noun phrase)
VP verb (VP verb phrase)
VP verb NP
S NP VP (S sentence)
Here, POS Tagging is included in the grammar.
Parsing (here: LR, bottom-up)
Determine the syntactic structure of the sentence:
“the dog eats the bone”
the det POS Tagging
dog noun
det noun NP Rule application
eats verb
the det
bone noun
det noun NP
verb NP VP
NP VP S
Syntax Analysis / Parsing
Syntactic Structure often represented as Parse Tree.
Connect symbols according to applied grammar rules (like Rewrite Systems).
Lexical Ambiguity
Several word senses or word categories
e.g. chase – noun or verb
e.g. plant - ????
Syntactic Ambiguity
Several parse trees:
1) “The dog eats the bone in the park.”
2) “The dog eats the bone in the package.”
Who/what is in the park and who/what is in the package?
Syntactically speaking:
How do I bind the Prepositional Phrase "in the ..." ?
Semantic Representation
Represent the meaning of a sentence.Generate, e.g.• a logic-based representation or • a frame-based representation
Fillmore’s case frames
based on the syntactic structure, lexical entries, and particularly the head-verb, which determines how to arrange parts of the sentence and relate them to each other in the semantic representation.
Semantic Representation
Verb-centered representation:
Verb (action, head) is regarded as center of verbal expression and determines the case frame with possible case roles; other parts of the sentence are described in relation to the action as fillers of case slots. (cf. also Schank’s CD Theory)
Typing of case roles is possible (e.g. 'agent' refers to a specific sort or concept, like “humans”)
General Frame for eat
Agent: animate
Action: eat
Patiens: food
Manner: {e.g. fast}
Location: {e.g. in the yard}
Time: {e.g. at noon}
Frame with fillers for sample sentence
Agent: the dog
Action: eat
Patiens: the bone / the bone in the package
Location: in the park
General Frame for drive Frame with fillers
Agent: animate Agent: she
Action: drive Action: drives
Patiens: vehicle Patiens: the convertible
Manner:{the way it is done} Manner: fast
Location: Location-spec Location: [in the] Rocky Mountains
Source: Location-spec Source: [from] home
Destination: Location-spec Destination: [to the] ASIC conference
Time: Time-spec Time: [in the] summer holiday
Pragmatics
Pragmatics includes context-related aspects of NL expressions (utterances).
These are in particular anaphoric references, elliptic expressions, deictic expressions, …
anaphoric references – refer to items mentioned before
deictic expressions – simulate pointing gestures
elliptic expressions – incomplete expression;
relate to item mentioned before
Pragmatics
“I put the box on the top shelve.”
“I know that. But I can’t find it there.”
deictic expressionanaphoric reference
Pragmatics
“I put the box on the top shelve.”
“I know that. But I can’t find it there.”
anaphoric reference
Pragmatics
“I put the box on the top shelve.”
“I know that. But I can’t find it there.”
deictic expression
Pragmatics
“I put the box on the top shelve.”
“I know that. But I can’t find it there.”
“The candy-box?”
elliptic expression
deictic expressionanaphoric reference
Intentions
One philosophical assumption is that natural language is used to achieve something:
“Do things with words.”
The meaning of an utterance is essentially determined by the intention of the speaker.
Intentionality - Examples
What was said: What was meant:
“There is a terrible "Can you please draft here.” close the window."
“How does it look "I am really mad; here?” clean up your room."
"Will this ever end?" "I would prefer to bewith my friends than to sit in class now."
Metaphors
The meaning of a sentence or expression is not directly inferable from the sentence structure and the word meanings. Metaphors transfer concepts and relations from one area of discourse into another area, for example, seeing time as a line (in space) or seeing friendship / life as a journey.
Metaphors - Examples
“This car eats a lot of gas.”
“She devoured the book.”
“He was tied up with his clients.”
“Marriage is like a journey.”
“Their marriage was a one-way road into hell.”
(see also George Lakoff, e.g. Women, Fire and Dangerous Things)
Discourse / Dialogue Structure
Grammar for various sentence types (speech acts): dialogue, discourse, story grammar
Distinguish questions, commands, and statements: Where is the remote-control? Bring the remote-control! The remote-control is on the brown table.
Dialogue Grammars describe possible sequences of Speech Acts in communication, e.g. that a question is followed by an answer/statement.
Similar for Discourse (like continuous texts).
Speech Processing SystemsTypes and Characteristics
Speech Recognition vs. Speaker Recognition (Voice Recognition; Speaker Identification )
speaker-dependent vs. speaker-independent training? unlimited vs. large vs. small vocabulary single word vs. continuous speech
Speech Recognition Phases
• acoustic signal as input
• signal analysis - spectrogram
• feature extraction
• phoneme recognition
• word recognition
• conversion into written words
Spoken Language
Output of Speech Recognition System as input "text".
Can be associated with probabilities for different word sequences.
Contains ungrammatical structures, so-called "disfluencies", e.g. repetitions and corrections.
Spoken Language - Examples
1. no [s-] straight southwest
2. right to [my] my left
3. [that is] that is correct
Robin J. Lickley. HCRC Disfluency Coding Manual. http://www.ling.ed.ac.uk/~robin/maptask/HCRCdsm-01.html
Spoken Language - Disfluency
Reparandum and Repair
Reparandum Repair
[come to] ... walk right to [the] ... the right-hand side of the page
Spoken Language - Example
1. we're going to [g-- ]... turn straight back around
for testing.
2. [come to] ... walk right to the ... right-hand side of the page.
3. right [up ... past] ... up on the left of the ... white mountain walk ... right up past.
4. [i'm still] ... i've still gone halfway back round the lake again.
Spoken Language - Example
1. [I’d] [d if] I need to go
2. [it’s basi--] see if you go over the old mill
3. [you are going] make a gradual slope … to your right
4. [I’ve got one] I don’t realize why it is there
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