A New Method of Voiced/Unvoiced Classification Based on Clustering

A New Method of Voiced/Unvoiced Classification Based on Clustering

In this paper, a new method for making v/uv decision is developed which uses a multi-feature v/uv classification algorithm based on the analysis of cepstral peak, zero crossing rate, and autocorrelation function (ACF) peak of short-time segments of the speech signal by using some clustering methods....

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Veröffentlicht in:Journal of signal and information processing 2011-11, Vol.2 (4), p.336-347
Hauptverfasser: Radmard, Mojtaba, Hadavi, Mahdi, Nayebi, Mohammad Mahdi
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Autocorrelation functions
Classification
Clustering
Data processing
Decision analysis
Segments
Speech
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Beschreibung
Zusammenfassung:In this paper, a new method for making v/uv decision is developed which uses a multi-feature v/uv classification algorithm based on the analysis of cepstral peak, zero crossing rate, and autocorrelation function (ACF) peak of short-time segments of the speech signal by using some clustering methods. This v/uv classifier achieved excellent results for identification of voiced and unvoiced segments of speech.
ISSN:2159-4465
2159-4481
DOI:10.4236/jsip.2011.24048