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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

MARC

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100 1 |a Herbig, Tobias.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Self-Learning Speaker Identification  |h [electronic resource] :  |b A System for Enhanced Speech Recognition /  |c by Tobias Herbig, Franz Gerl, Wolfgang Minker. 
250 |a 1st ed. 2011. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2011. 
300 |a XII, 172 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Signals and Communication Technology,  |x 1860-4870 
505 0 |a Introduction -- State of the Art -- Fundamentals -- Speech Production -- Front-End -- Speaker Change -- Speaker Identification.-Speaker Adaptation. 
520 |a 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. 
650 0 |a Signal processing. 
650 0 |a Biometric identification. 
650 0 |a Telecommunication. 
650 0 |a User interfaces (Computer systems). 
650 0 |a Human-computer interaction. 
650 1 4 |a Signal, Speech and Image Processing . 
650 2 4 |a Biometrics. 
650 2 4 |a Communications Engineering, Networks. 
650 2 4 |a User Interfaces and Human Computer Interaction. 
700 1 |a Gerl, Franz.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Minker, Wolfgang.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783642268809 
776 0 8 |i Printed edition:  |z 9783642198984 
776 0 8 |i Printed edition:  |z 9783642199004 
830 0 |a Signals and Communication Technology,  |x 1860-4870 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-642-19899-1  |z Texto Completo 
912 |a ZDB-2-ENG 
912 |a ZDB-2-SXE 
950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712)