11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

A Language-Identification Inspired Method for Spontaneous Speech Detection

Mickael Rouvier (1), Richard Dufour (2), Georges Linarès (1), Yannick Estève (2)

(1) LIA, University of Avignon, France
(2) LIUM, University of Le Mans, France

Most of spontaneous speech detection systems relies on disfluency analysis or on combination of acoustic and linguistic features. This paper presents a method that considers spontaneous speech as a specific language, which could be identified by using language-recognition methods, such as shifted delta cepstrum parameters, dimensionality reduction by linear discriminant analysis and factor-analysis based filtering process. Experiments are conducted on the French EPAC corpus. On a 3 spontaneity-level task, this approach obtains a relative gain of about 22% of identification rates, in comparison to the classical MFCC/GMM technique. Then, we combine these techniques to others previously proposed for spontaneous speech detection. Finally, the proposed system obtains a recognition rate of 65% on high spontaneous speech segments.

Full Paper

Bibliographic reference.  Rouvier, Mickael / Dufour, Richard / Linarès, Georges / Estève, Yannick (2010): "A language-identification inspired method for spontaneous speech detection", In INTERSPEECH-2010, 1149-1152.