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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 4/2017

14.09.2017

Arabic stop consonants characterisation and classification using the normalized energy in frequency bands

verfasst von: Karim Tahiry, Badia Mounir, Ilham Mounir, Laila Elmazouzi, Abdelmajid Farchi

Erschienen in: International Journal of Speech Technology | Ausgabe 4/2017

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Abstract

In general, speech is made with sequences of consonants (fricatives, nasals and stops), vowels and glides. The classification of the stop consonants remains one of the most challenging problems in speech recognition. In this paper, we propose a new approach based on the normalized energy in frequency bands in the release and closure phases in order to characterize and classify the Arabic stop consonants (/b/, /d/, /t/, /k/ and /q/) and to recognize the CV syllable. Classification experiments were performed using decision algorithms on stop consonants C and CV syllables extracted from an Arabic corpus. The results yielded to an overall stop consonants classification of 90.27% and syllables CV recognition upper than 90% for all stops.
Vorheriger Artikel Factored front-end CMLLR for joint speaker and environment normalization under DNN-HMM
Nächster Artikel Spoken character classification using abductive network

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Metadaten
Titel
Arabic stop consonants characterisation and classification using the normalized energy in frequency bands
verfasst von
Karim Tahiry
Badia Mounir
Ilham Mounir
Laila Elmazouzi
Abdelmajid Farchi
Publikationsdatum
14.09.2017
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 4/2017
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-017-9454-9

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