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

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 ov...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Herbig, Tobias (Autor), Gerl, Franz (Autor), Minker, Wolfgang (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.
Edición:1st ed. 2011.
Colección:Signals and Communication Technology,
Temas:
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:XII, 172 p. online resource.
ISBN:9783642198991
ISSN:1860-4870