Title: Discourse and Pragmatics
1Discourse and Pragmatics
- Dr. Björn Gambäck
- SICS Swedish Institute of Computer Science AB
- Stockholm, Sweden
2DUMAS
- Dynamic
- Universal
- Mobility
- for Adaptive
- Speech Interfaces
- Contact dumas_at_sics.se
3DUMAS Facts
- Development and research project on multilingual,
adaptive speech interfaces - Demo application AthosMail
- (e-mail with a dialogue interface over mobile
phone) - 3-year project
- started October 2001
- finishes September 2004
- Budget 3,56 million euro (ca 50 million birr)
- 8 members in 4 different countries
4Motivation
- Interactive applications are a technological and
commercial possibility - However
- Incapability to process structured text
- Limited conversational abilities
- Limited user models
5Objectives
- Dynamic intelligent interaction capabilities
- Universal various users, situations and formats
- Mobility mobile applications
- for
- Adaptive user habits and preferences
- Speech text and speech, multilinguality
- interfaces agent-based architecture
6Athos Speech Interfaces
- are adaptable to the situation, domain and user
- can be used for various mobile applications
- exploit learning techniques to adapt to a
particular users preferences - can handle and produce both speech and text in
several languages - are instances of a flexible agent architecture
7Key Research Areas
- Agent-based development platform
- Athos architecture for speech applications
- Agents, evaluators, managers
- Exploration of machine learning techniques
- Reinforcement learning user interaction
strategies - Vector-based methods user priorities, interests
- Dialogue management
- Scenario-based corpus collection in 3 languages
- Dialogue act classification
- Annotation, AG format
8Key Research Areas, cont.
- Text parsing and analysis
- Robust and multilingual analysis
- User modelling
- Preferences and characteristics of the user
- Presentation techniques
- Provide information in a pleasant and intelligent
way - Input handling techniques
- Speech errors, multilingual input
9Talking to AthosMail
- U I want to listen to my messages.
- A You have two new messages, one from Anders
about plans and one from Markku about Integration
Issues. - U Lets hear the one from Anders.
- A Message content Ill pick the children up
from the daycare centre at four today so if we
should discuss changes its good if we do it
right away. Anders. End of message. - U Read the message from Markku.
- A Message content Dear all, the latest version
of the User Modelling Agent is available on the
CVS. Please download it and make sure it works
with... - U Stop!
- Can I hear the one Anna sent yesterday instead?
10Linguistic Meaning (Gottlob Frege, 1848-1925)
- Giving an account of linguistic meaning
describing the meanings of complete sentences - Explaining the meaning of a sentence S
explaining under which conditions S is true - Explaining the meanings of other units describe
how they contribute to Ss meaning
11Linguistic Meaning (Donald Davidson, 1915- )
- The truth values of the sentences are determined
by their syntactic structure. - The meanings of component words is all that a
theory of meaning for a language can deliver.
12Linguistic Meaning (Hans Kamp, 194?- )
- A theory of meaning must also say things about
interpretation. - A speakers grasp of the meaning of a language
depends on his ability to interpret sentences he
hear. - Truth and interpretation are intimately
connected.
13Discourse Representation Structures (DRSs)
- (instead of using first-order representations)
- DRSs are obtained through the application of
certain rules to the input sentences. - These rules do not look just at the current
sentence, but also at DRSs that already has been
built.
14Components of DRSs
- a list of discourse referents
- a list of conditions
- If d1, , dn are discourse referents (n gt 0)
- and c1, , cm (m gt 0) are conditions then
-
- is a DRS.
d1, , dn
c1 cm
15Indefinites
x
WOMAN(x) SNORE(x)
X discourse referent from the NP a woman The
VP adds the condition SNORE(x)
16Proper Names
x
xVINCENT ?
DIE(x)
Proper names also introduce discourse referents
17Universal Quantification
- every man snores
- (?x(MAN(x) ? SNORE(x))
x
?
MAN(x)
SNORE(x)
18Reference
- Relationship between linguistic elements (words,
etc.) - and the non-linguistic world of experience.
- Indicates which things in the world are talked
about. - The same expression can refer to different things
- (e.g. your left ear)
- Two different expression can have the same
referent - (e.g., the Morning Star and the Evening Star)
19Reference, cont.
- Anaphoric reference
- the element referred to has been mentioned
before - Antecedent
- the element referred to by the anaphor
-
- John went to the cinema.
- He goes there often.
- John went to the cinema.
- He goes there often.
20Pronouns
- Deictic
- accompanied by a deictic act
- (e.g., pointing a finger)
- Anaphoric
- referring to some item mentioned elsewhere
- (the antecedent)
21Pronoun Resolution
- Salience (recency)
- John has a Fiat.
- Mary has a Ford.
- Betty likes to drive it.
- Selectional restrictions
- John has a Fiat.
- Betty likes it.
- Betty likes him.
22John watches Big Brother.It fascinates him.
- John watches Big Brother.
x
x y
S
JOHN(x) x watches Big Brother
john watches Big Brother
JOHN(x) BIG BROTHER(y) x watches y
VP
NPmale
NPhum
V
John
x
watches
Big Brother
y
watches Big Brother reducible condition
A proper name introduces a reference marker
23John watches Big Brother.It fascinates him.
x y
x y u v
x y u
S
JOHN(x) BIG BROTHER(y) x watches y it fascinates
him
JOHN(x) BIG BROTHER(y) x watches y u y u
fascinates him
JOHN(x) BIG BROTHER(y) x watches y u y v x u
fascinates v
VP
NPhum
NPmale
V
It
u
fascinates
him
v
A pronoun introduces a reference marker and a
condition ?? where ? is a suitable marker
24Text Coherence
- John hid Bills car keys. He got angry.
- John hid Bills car keys. He was drunk.
- John hid Bills car keys. He likes spinach.
- Coherence relations
- Result S1 ? S2
- Explanation S2 ? S1
- (and many more)
25Dialogue
- Turn-taking
- Utterances
- Dialogue Acts
- GREETING
- REQUEST
- QUESTION
- ANSWER
- COMMAND
- Span one or more utterances
26Conversational Implicature (Grice)
- Quantity
- Be exactly as informative as required
- Quality
- Be true
- Relevance
- Be relevant
- Manner
- Be perspicuous (avoid ambiguity, etc)
27Dialogue Structure
- Hi! GREETING
- Hi there, whats up? GREETING, QUEST
- Not much. Did you see the game? ANSWER, QUEST
- Yeah, but they were lousy. CONFIRM, STMNT
- Mmm CONFIRM
- Ok, see you later. CLOSING
- Later, dude! CLOSING
28Dialogue Management
- System driven (system initiative)
- Prompting
- Slot-filling (frames/templates)
- Finite-state automaton
- User driven
- Mixed-initiative
- (goal oriented)
29Human-Computer Conversation(Wilks Catizone)
- CONVERSE
- Top-down control of conversation (scripts)
- Large-scale linguistic resources (dictionaries)
- Catherine, 26-year old editor
- Loebner Prize winner 1997
30Conversational InterfacesAdvances and
Challenges (Zue Glass)
- Mixed-initiative
- Learning
- Robustness
- Dialogue management
- Misunderstandings
- Portability
31User Modelling in AthosMail
- Record user characteristics and actions
- Enable the system to tailor its responses
- Give expectations of
- user vocabulary
- likely next actions
32Construction of Semantic Representations
- Three basic principles
- Lexicalization
- try to keep semantic information lexicalized
- Compositionality
- pass information up compositionally from
terminals - Underspecification
- Dont make a choice unless you have to
- (the interpretation of ambiguous parts is left
unresolved)
33Underspecification
- A meaning ? of a formalism L is underspecified
- represents an ambiguous sentence in a more
compact manner than by a disjunction of all
readings - L is complete Ls disambiguation device
produces all possible refinements of any ? - Example
- consider a sentence with 3 quantified NPs
- (with underspecifed scoping relations)
- L must be able to represent all 23! 64
refinements - (partial and complete disambiguations) of the
sentence.
34Phenomena for Underspecification
- local ambiguities
- e.g., lexical ambiguities, anaphoric or deictic
use of PRO - global ambiguities
- e.g., scopal ambiguities, collective-distributive
readings - ambiguous or incoherent non-semantic information
- e.g., PP-attachment, number disagreement
35Lexical ambiguity
Some English words with many senses (from
Merriam-Webster Pocket Dictionary) Word Category
Senses go verb 63 run verb 35 way
noun 31 do verb 30 form noun
24 take verb 24 dead adjective 21
36Underspecified Semantic Representations
- Reyle Underspecified Discourse Representation
Structures - Bos Labelled Underspecified Discourse Structures
- Object Language Kamps Discourse Representation
Structures - Underspecified w.r.t. scope of quantifying
expressions - One underspecified representation describes
several DRSs