Model Selection Criteria for Acoustic Segmentation
نویسندگان
چکیده
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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