Paper Info
Title
Construction of Back-Channel Utterance Corpus for Responsive Spoken Dialogue System Development
Abstract
In spoken dialogues, if a spoken dialogue system does not respond at all during user's utterances, the user might feel uneasy because the user does not know whether or not the system has recognized the utterances. In particular, back-channel utterances, which the system outputs as voices such as "yeah" and "uh huh" in English have important roles for a driver in in-car speech dialogues because the driver does not look towards a listener while driving. This paper describes construction of a back-channel utterance corpus and its analysis to develop the system which can output back-channel utterances at the proper timing in the responsive in-car speech dialogue. First, we constructed the back-channel utterance corpus by integrating the back-channel utterances that four subjects provided for the driver's utterances in 60 dialogues in the CIAIR in-car speech dialogue corpus. Next, we analyzed the corpus and revealed the relation between back-channel utterance timings and information on bunsetsu, clause, pause and rate of speech. Based on the analysis, we examined the possibility of detecting back-channel utterance timings by machine learning technique. As the result of the experiment, we confirmed that our technique achieved as same detection capability as a human.
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
machine learning
Field
DocType
Citations 
Computer science,Utterance,Speech recognition,Natural language processing,Artificial intelligence,System development,Back channel,Feel Uneasy
Conference
2
PageRank 
References 
Authors
0.66
5
4
Name
Order
Citations
PageRank
Yuki Kamiya1102.98
Tomohiro Ohno23110.06
Shigeki Matsubara317943.41
Hideki Kashioka438067.59