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Article Dans Une Revue Journal of Voice Année : 2022

Automated Assessment of Glottal Dysfunction Through Unified Acoustic Voice Analysis

Résumé

This paper uses the recent glottal flow model for iterative adaptive inverse filtering to analyze recordings from dysfunctional speakers, namely those with larynx-related impairment such as laryngectomy. The analytical model allows extraction of the voice source spectrum, described by a compact set of parameters. This single model is used to visualize and better understand speech production characteristics across impaired and nonimpaired voices. The analysis reveals some discriminative aspects of the source model which map to a physiological class description of those impairments. Furthermore, being based on analysis of source parameters only, it is complementary to any existing techniques of vocal-tract or phonetic analysis. The results indicate the potential for future automated speech reconstruction systems that adapt to the method of reconstruction required, as well as being useful for mainstream speech systems, such as ASR, in which front-end analysis can direct back-end models to suit characteristics of impaired speech.
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Dates et versions

hal-02987882 , version 1 (20-11-2020)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Ian Vince Mcloughlin, Olivier Perrotin, Hamid Sharifzadeh, Jacqui Allen, Yan Song. Automated Assessment of Glottal Dysfunction Through Unified Acoustic Voice Analysis. Journal of Voice, 2022, 36 (6), pp.743-754. ⟨10.1016/j.jvoice.2020.08.032⟩. ⟨hal-02987882v1⟩
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