Human and Automatic Speaker Recognition over Telecommunication Channels
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Beschreibung
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.
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.
Addresses the evaluation of the human and the automatic performances under different channel distortions Demonstrates the benefits of communication channels of extended bandwidth Delivers an insight into how speaker-specific characteristics of speech are preserved through different transmissions Motivates speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband Includes supplementary material: sn.pub/extras
Autor*in
Laura Fernández Gallardo
Themen in »Human and Automatic Speaker Recognition over Telecommunication Channels«
Channel Distortions Electro-acoustic User Interfaces Gaussian Mixture Models-Universal Background Model Human Speaker Identification Joint Factor Analysis Speaker Verification i-vectors