Download presentation
Presentation is loading. Please wait.
Published byAugustus Hamilton Modified over 9 years ago
1
CONVERSE Intelligent Research Ltd. David Levy, Bobby Batacharia University of Sheffield Yorick Wilks, Roberta Catizone, Alex Krotov
2
Converse What is CONVERSE? A conversation program designed for the Loebner competition in 1997. What is the Loebner competion? –Turing test where a number of judges converse with the submitted programs using a keyboard. They then decide which of the programs is the most real (One of the entrants is a real person sitting behind a terminal in another room). We won
3
Converse What is CONVERSE Script driven system that tries to keep control of the conversation by posing questions to the user.
4
Converse Character Personality Catherine, a 26 year-old female journalist Born in Britain, living in New York We store information about Catherine in a Database.
5
Converse Technical Details Written in C and C++ Runs under Windows 95 Modular System Architecture Can converse on 60 different topics –Abortion, work, travel, death, religion, gun- control... Speech component was added later for output
6
Converse System Architecture Input Modules Data Modules Action Modules
7
Converse
8
Input Modules Pre-processing Parser Micro-Queries
9
Converse Preprocessing Spell checker Elision expansion Name tagger Punctuation correction
10
Converse Parser Prospero Parser (off the shelf) –Tags part of speech –Parses the input Parser Post Processor (PPP) –Flattens the parse tree –Corrects deficiencies of Prospero
11
Converse MicroQueries Defines a set of patterns (to be mapped on to the scripts eventually). Individual patterns are connected to each other with logical functions. Access to the input as well as Wordnet functions.
12
Converse Data Modules Person Database (PDB) –Stores all the information for each user –Stores information about the system character Wordnet –Synonyms and word definitions Collins –Famous people, places and things
13
Converse Action Modules Where-to-Go Pisces Special Cases Scripts Information Scavenger Topic Change Generator
14
Converse Where-to Go Module Dispatcher module that decides which of the action modules should handle an utterance. Each action module places a bid (indicating the confidence that it has a valid response) and the highest bid wins. An action module can extract data from the input and store it in the database.
15
Converse Pisces Question Answering Module Divided into 2 parts - question recognition and question answering Contains twenty different question types Questions are answered by first consulting the person database Wordnet is used to enrich the search and for definitions.
16
Converse Pisces Collins is used for famous entities - people and places. If a response cannot be formulated, then a filler response is given. The filler responses are typed according to the question type. We distinguish WH questions from other question types.
17
Converse Special Cases Handles exceptional cases – rude language –illogical birthdays or age –Talk about sex –Violence A response is triggered from a set of canned phrases for the above categories.
18
Converse Script Module Guides the conversation through a network of script lines Each script line has –Some canned text –Links to other related scripts and –A set of Microqueries (patterns that map onto the scripts) Keeps track of what the system has said to avoid repeats.
19
Converse Information Scavenger Extracts any possible information from an user utterance if it is a statement. It is only activated if no other action modules have extracted information from the current utterance.
20
Converse Topic Change Module Controls the flow of conversation Decides what order the available 60 topics should be presented to the user. Can be triggered by the user. –The system uses content words from the user’s response to try to match to topic keywords
21
Converse Generator Takes the results of the action modules and assembles then into a coherent utterance. Uses information from the Person Database where necessary. Connectives are added where need to ensure a smooth flowing respons. Consults a module that provides a number of different ways to say the same thing.
22
Converse Limitations Parser not meant for dialogue We don’t really take into account the user’s previous utterances even though we have kept a dialogue history. Doesn’t have an inference engine.
23
Converse Advantages Flexible design - modular architecture Person database allows for swapping of different system personalities Has hooks for incorporating large data resources (encyclopedias, knowledge bases etc.)
24
Converse Applications Virtual friend Toy interface Front-end to a relational Database Front-end to a software help system
Similar presentations
© 2025 SlidePlayer.com Inc.
All rights reserved.