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Voice activity detection using generalized gamma distribution

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2006) 3955 LNAI 3-12
DOI: 10.1007/11752912_3
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Abstract

In this work, we model speech samples with a two-sided generalized Gamma distribution and evaluate its efficiency for voice activity detection. Using a computationally inexpensive maximum likelihood approach, we employ the Bayesian Information Criterion for identifying the phoneme boundaries in noisy speech. © Springer-Verlag Berlin Heidelberg 2006.

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Almpanidis, G., & Kotropoulos, C. (2006). Voice activity detection using generalized gamma distribution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3955 LNAI, pp. 3–12). Springer Verlag. https://doi.org/10.1007/11752912_3

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