A Shallow Model of Backchannel Continuers in Spoken Dialogue

Nicola Cathcart, Jean Carletta, Ewan Klein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spoken dialogue systems would be more acceptable if they were able to produce backchannel continuers such as mm-hmm in naturalistic locations during the user's utterances. Using the HCRC Map Task Corpus as our data source, we describe models for predicting these locations using only limited processing and features of the user's speech that are commonly available, and which therefore could be used as a low-cost improvement for current systems. The baseline model inserts continuers after a predetermined number of words. One further model correlates back-channel continuers with pause duration, while a second predicts their occurrence using trigram POS frequencies. Combining these two models gives the best results.
Original languageEnglish
Title of host publicationProceedings of the Tenth Conference on European Chapter of the Association for Computational Linguistics - Volume 1
Place of PublicationStroudsburg, PA, USA
PublisherAssociation for Computational Linguistics
Pages51-58
Number of pages8
ISBN (Print)1-333-56789-0
DOIs
Publication statusPublished - 2003
Event10th Conference of the European Chapter of the Association for Computational Linguistics (EACL) 2003 - Agro Hotel, Budapest, Hungary
Duration: 12 Apr 200317 Apr 2003

Publication series

NameEACL '03
PublisherAssociation for Computational Linguistics

Conference

Conference10th Conference of the European Chapter of the Association for Computational Linguistics (EACL) 2003
Country/TerritoryHungary
CityBudapest
Period12/04/0317/04/03

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