Details

Autor(en) / Beteiligte

• KOMATANI, Kazunori
• HOTTA, Naoki
• SATO, Satoshi
• NAKANO, Mikio

Titel

Posteriori Restoration of Turn-Taking and ASR Results for Incorrectly Segmented Utterances

Ist Teil von

• IEICE Transactions on Information and Systems, 2015/11/01, Vol.E98.D(11), pp.1923-1931

Ort / Verlag

The Institute of Electronics, Information and Communication Engineers

Erscheinungsjahr

2015

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Appropriate turn-taking is important in spoken dialogue systems as well as generating correct responses. Especially if the dialogue features quick responses, a user utterance is often incorrectly segmented due to short pauses within it by voice activity detection (VAD). Incorrectly segmented utterances cause problems both in the automatic speech recognition (ASR) results and turn-taking: i.e., an incorrect VAD result leads to ASR errors and causes the system to start responding though the user is still speaking. We develop a method that performs a posteriori restoration for incorrectly segmented utterances and implement it as a plug-in for the MMDAgent open-source software. A crucial part of the method is to classify whether the restoration is required or not. We cast it as a binary classification problem of detecting originally single utterances from pairs of utterance fragments. Various features are used representing timing, prosody, and ASR result information. Experiments show that the proposed method outperformed a baseline with manually-selected features by 4.8% and 3.9% in cross-domain evaluations with two domains. More detailed analysis revealed that the dominant and domain-independent features were utterance intervals and results from the Gaussian mixture model (GMM).