ASR2000 - Automatic Speech Recognition: Challenges for the new Millenium September 18-20, 2000 Paris, France

Model Selection Criteria for Acoustic Segmentation

Mauro Cettolo and Marcello Federico

ITC-irst - Centro per la Ricerca Scientifica e Tecnologica, Povo, Trento, Italy

Robust acoustic segmentation has become a critical issue in order to apply speech recognition to audio streams with variable acoustic content, e.g. radio programs. Many techniques in the literature base segmentation on statistical model selection, by applying the Bayesian Information Criterion. This work reviews alternative model selection criteria and presents comparative experiments both under controlled conditions and on a broadcast news corpus.

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Bibliographic reference.  Cettolo, Mauro / Federico, Marcello (2000): "Model Selection Criteria for Acoustic Segmentation", In ASR-2000, 221-227.