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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 1/2019

03.12.2018

Speech synthesis for glottal activity region processing

verfasst von: Nagaraj Adiga, S. R. M Prasanna

Erschienen in: International Journal of Speech Technology | Ausgabe 1/2019

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Abstract

The objective of this paper is to demonstrate the significance of combining different features present in the glottal activity region for statistical parametric speech synthesis (SPSS). Different features present in the glottal activity regions are broadly categorized as F0, system, and source features, which represent the quality of speech. F0 feature is computed from zero frequency filter and system feature is computed from 2-D based Riesz transform. Source features include aperiodicity and phase component. Aperiodicity component representing the amount of aperiodic component present in a frame is computed from Riesz transform, whereas, phase component is computed by modeling integrated linear prediction residual. The combined features resulted in better quality compared to STRAIGHT based SPSS both in terms of objective and subjective evaluation. Further, the proposed method is extended to two Indian languages, namely, Assamese and Manipuri, which shows similar improvement in quality.
Vorheriger Artikel Optimal prosodic feature extraction and classification in parametric excitation source information for Indian language identification using neural network based Q-learning algorithm
Nächster Artikel Hidden-Markov-model based statistical parametric speech synthesis for Marathi with optimal number of hidden states

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Fußnoten
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Metadaten
Titel
Speech synthesis for glottal activity region processing
verfasst von
Nagaraj Adiga
S. R. M Prasanna
Publikationsdatum
03.12.2018
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 1/2019
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-018-09583-5

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