Agreement and disagreement utterance detection in conversational speech by extracting and integrating local features
Agreement and disagreement utterance detection in conversational speech by extracting and integrating local features
复制标题
通过提取和集成局部特征来检测会话语音中的同意和分歧话语
DOI：
10.21437/interspeech.2015-538
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Sumitaka Sakauchi
中科院分区：
文献类型：
--
作者：
Atsushi Ando;Taichi Asami;M. Okamoto;H. Masataki;Sumitaka Sakauchi
本文提出了一种新的框架，自动检测自然会话中的同意和不同意的话语。这样的功能对于诸如会议摘要的会话理解是至关重要的。自然会话中一致和不一致话语检测的难点之一是话语单元中的歧义。话语通常被短暂的停顿打断。然而，在谈话中，往往是一口气说出多个句子。这些话语只是在某些部分而不是整个话语中表现出同意和不同意的特征。这使得传统的方法存在问题，因为它们假设每个话语只是一个句子，并从整个话语中提取全局特征。为了解决这个问题，我们提出了一个检测框架，只利用本地韵律/词汇功能。局部特征是从仅覆盖几个单词的短窗口中提取的。同意、不同意和其他的后验概率是逐个窗口估计的，并被整合以产生最终决策。对自由讨论语音的实验表明，该方法通过使用局部特征，在检测同意和不同意的话语时提供了更高的准确性。
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 utter-ance. To deal with this problem, we propose a detection framework that utilizes only local prosodic/lexical features. The lo-cal 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 fi-nal 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.