Self-Learning Speaker Identification: A System for Enhanced Speech Recognition

Self-Learning Speaker Identification: A System for Enhanced Speech Recognition

by Tobias Herbig, Franz Gerl, Wolfgang Minker
     
 

Current speech recognition systems suffer from variation of voice characteristics between speakers as they are usually based on speaker independent speech models. In order to resolve this issue, adaptation methods have been developed in many state-of-the-art systems. However,
information acquired over time is still lost whenever another speaker intermittently

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Overview

Current speech recognition systems suffer from variation of voice characteristics between speakers as they are usually based on speaker independent speech models. In order to resolve this issue, adaptation methods have been developed in many state-of-the-art systems. However,
information acquired over time is still lost whenever another speaker intermittently uses the recognition system. This work therefore develops an integrated approach for speech and speaker recognition in order to improve the self-learning opportunities of the system. A speaker adaptation scheme is introduced. It is suited for fast short-term and detailed long-term adaptation. These adaptation profiles are then used for an efficient speaker recognition system. The speaker identification enables the speaker adaptation to track different speakers which results in an optimal long-term adaptation.

Product Details

ISBN-13:
9783642268809
Publisher:
Springer Berlin Heidelberg
Publication date:
08/28/2013
Series:
Signals and Communication Technology
Edition description:
2011
Pages:
172
Product dimensions:
6.14(w) x 9.21(h) x 0.40(d)

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