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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 4/2013

01.12.2013

Pitch synchronous and glottal closure based speech analysis for language recognition

verfasst von: K. Sreenivasa Rao, Sudhamay Maity, V. Ramu Reddy

Erschienen in: International Journal of Speech Technology | Ausgabe 4/2013

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Abstract

This paper explores pitch synchronous and glottal closure (GC) based spectral features for analyzing the language specific information present in speech. For determining pitch cycles (for pitch synchronous analysis) and GC regions, instants of significant excitation (ISE) are used. The ISE correspond to the instants of glottal closure (epochs) in the case of voiced speech, and some random excitations like onset of burst in the case of nonvoiced speech. For analyzing the language specific information in the proposed features, Indian language speech database (IITKGP-MLILSC) is used. Gaussian mixture models are used to capture the language specific information from the proposed features. Proposed pitch synchronous and glottal closure spectral features are evaluated using language recognition studies. The evaluation results indicate that language recognition performance is better with pitch synchronous and GC based spectral features compared to conventional spectral features derived through block processing. GC based spectral features are found to be more robust against degradations due to background noise. Performance of proposed features is also analyzed on standard Oregon Graduate Institute Multi-Language Telephone-based Speech (OGI-MLTS) database.
Vorheriger Artikel Wavelet fuzzy LVQ based speaker verification system
Nächster Artikel Performance evaluation of a wavelet-based pitch detection scheme

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Metadaten
Titel
Pitch synchronous and glottal closure based speech analysis for language recognition
verfasst von
K. Sreenivasa Rao
Sudhamay Maity
V. Ramu Reddy
Publikationsdatum
01.12.2013
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 4/2013
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-013-9193-5

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