14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Detecting Laughter and Filled Pauses Using Syllable-Based Features

Gouzhen An, David Guy Brizan, Andrew Rosenberg

CUNY Graduate Center, USA

Identifying laughter and filled pauses is important to understanding spontaneous human speech. These are two common vocal expressions that are non-lexical and incredibly communicative. In this paper, we use a two-tiered system for identifying laughter and filled pauses. We first generate frame level hypotheses and subsequently rescore these based on features derived from acoustic syllable segmentation. Using Interspeech 2013 ComParE challenge corpus, SVC, we find that these rescoring experiments and inclusion of syllable based acoustic/prosodic features allow for the detection of laughter and filled pauses by at 89.3% UAAUC on the development set, an improvement of 1.7% over the challenge baseline.

Full Paper

Bibliographic reference.  An, Gouzhen / Brizan, David Guy / Rosenberg, Andrew (2013): "Detecting laughter and filled pauses using syllable-based features", In INTERSPEECH-2013, 178-181.