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Human and Automatic Speaker Recognition over Telecommunication Channels [electronic resource] / by Laura Fernández Gallardo.

By: Fernández Gallardo, Laura [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: T-Labs Series in Telecommunication Services: Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XII, 169 p. 34 illus., 32 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789812877277.Subject(s): Signal processing | Signal, Speech and Image ProcessingAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
Introduction -- Literature Review -- Human Speaker Identification Performance under Channel Degradations -- Importance of Intelligible Phonemes for Human Speaker Recognition in Different Bandwidths -- Automatic Speaker Verification Performance Under Channel Distortions -- Detecting Speaker-Discriminative Spectral Content in Wideband for Automatic Speaker Recognition -- Relations Among Speech Quality, Human Speaker Identification, and Automatic Speaker Verification. Conclusions and Future Work.
In: Springer Nature eBookSummary: This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Its main contribution is the demonstration of the benefits of communication channels of extended bandwidth, together with an insight into how speaker-specific characteristics of speech are preserved through different transmissions. It provides sufficient motivation for considering speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband.
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Introduction -- Literature Review -- Human Speaker Identification Performance under Channel Degradations -- Importance of Intelligible Phonemes for Human Speaker Recognition in Different Bandwidths -- Automatic Speaker Verification Performance Under Channel Distortions -- Detecting Speaker-Discriminative Spectral Content in Wideband for Automatic Speaker Recognition -- Relations Among Speech Quality, Human Speaker Identification, and Automatic Speaker Verification. Conclusions and Future Work.

This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Its main contribution is the demonstration of the benefits of communication channels of extended bandwidth, together with an insight into how speaker-specific characteristics of speech are preserved through different transmissions. It provides sufficient motivation for considering speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband.

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