Voice Activity Detection Using Generalized Gamma Distribution | Zendy

George Almpanidis | Zendy; Constantine Kotropoulos | Zendy

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Voice Activity Detection Using Generalized Gamma Distribution

Author(s) -

George Almpanidis,

Constantine Kotropoulos

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-34117-X

DOI - 10.1007/11752912_3

Subject(s) - computer science , generalized gamma distribution , gamma distribution , voice activity detection , bayesian probability , speech recognition , maximum likelihood , distribution (mathematics) , inverse gamma distribution , artificial intelligence , pattern recognition (psychology) , speech processing , probability distribution , algorithm , statistics , mathematics , distribution fitting , inverse chi squared distribution , mathematical analysis

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.

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