An Overview of Noise-Robust Automatic Speech Recognition
- Author
- JINYU LI1 ; LI DENG1 ; YIFAN GONG1 ; HAEB-UMBACH, Reinhold2
[1] Microsoft Corporation, Redmond, WA 98052-6399, United States
[2] Department of Communications Engineering, University of Paderborn, 33098 Paderborn, Germany - Source
IEEE/ACM transactions on audio, speech, and language processing. 2014, Vol 22, Num 3-4, pp 745-777, 33 p ; ref : 292 ref
- ISSNNV
- 2329-9290
- Scientific domain
- Telecommunications
- Publisher
- IEEE, Piscataway, NJ
- Publication country
- United States
- Document type
- Article
- Language
- English
- Author keyword
- Speech recognition compensation distortion modeling joint model training noise robustness uncertainty processing
- Keyword (fr)
- Apprentissage Article synthèse Evaluation performance Immunité bruit Lecteur Modèle déterministe Modélisation Reconnaissance automatique Reconnaissance parole Robustesse Traitement parole
- Keyword (en)
- Learning Review Performance evaluation Noise immunity Reader Deterministic model Modeling Automatic recognition Speech recognition Robustness Speech processing
- Keyword (es)
- Aprendizaje Artículo síntesis Evaluación prestación Inmunidad ruido Lector Modelo determinista Modelización Reconocimiento automático Reconocimiento voz Robustez Tratamiento palabra
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D04 Telecommunications and information theory / 001D04A Information, signal and communications theory / 001D04A05 Signal processing / 001D04A05B Speech processing
- Discipline
- Telecommunications and information theory
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 28410310
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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