Paper Info
Title
Agreement And Disagreement Utterance Detection In Conversational Speech By Extracting And Integrating Local Features
Abstract
This paper presents a novel framework to automatically detect agreement and disagreement utterances in natural conversation. Such a function is critical for conversation understanding such as meeting summarization. One of the difficulties of agreement and disagreement utterance detection in natural conversation is ambiguity in the utterance unit. Utterances are usually segmented by short pauses. However, in conversations, multiple sentences are often uttered in one breath. Such utterances exhibit the characteristics of agreement and disagreement only in some parts, not the whole utterance. This makes conventional methods problematic since they assume each utterance is just one sentence and extract global features from the whole utterance. To deal with this problem, we propose a detection framework that utilizes only local prosodic/lexical features. The local features are extracted from short windows that cover just a few words. Posteriors of agreement, disagreement and others are estimated window-by-window and integrated to yield a final decision. Experiments on free discussion speech show that the proposed method, through its use of local features, offers significantly higher accuracy in detecting agreement and disagreement utterances.
Year
Venue
Keywords
2015
16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5
agreement and disagreement utterance detection, paralinguistics, conversational speech, local features
Field
DocType
Citations 
Computer science,Utterance,Speech recognition
Conference
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Atsushi Ando165.58
Taichi Asami22210.49
Manabu Okamoto301.01
Hirokazu Masataki4189.21
Sumitaka Sakauchi5368.30