Techniques for Noise Robustness in Automatic Speech Recognition (PDF)
(Sprache: Englisch)
Automatic speech recognition (ASR) systems are findingincreasing use in everyday life. Many of the commonplaceenvironments where the systems are used are noisy, for exampleusers calling up a voice search system from a busy cafeteria or astreet. This can...
sofort als Download lieferbar
eBook (pdf)
103.99 €
51 DeutschlandCard Punkte
sammeln
- Kauf auf Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Techniques for Noise Robustness in Automatic Speech Recognition (PDF)“
Automatic speech recognition (ASR) systems are findingincreasing use in everyday life. Many of the commonplaceenvironments where the systems are used are noisy, for exampleusers calling up a voice search system from a busy cafeteria or astreet. This can result in degraded speech recordings and adverselyaffect the performance of speech recognition systems. As theuse of ASR systems increases, knowledge of the state-of-the-art intechniques to deal with such problems becomes critical to systemand application engineers and researchers who work with or on ASRtechnologies. This book presents a comprehensive survey of thestate-of-the-art in techniques used to improve the robustness ofspeech recognition systems to these degrading externalinfluences.
Key features:
* Reviews all the main noise robust ASR approaches, includingsignal separation, voice activity detection, robust featureextraction, model compensation and adaptation, missing datatechniques and recognition of reverberant speech.
* Acts as a timely exposition of the topic in light of morewidespread use in the future of ASR technology in challengingenvironments.
* Addresses robustness issues and signal degradation which areboth key requirements for practitioners of ASR.
* Includes contributions from top ASR researchers from leadingresearch units in the field
Key features:
* Reviews all the main noise robust ASR approaches, includingsignal separation, voice activity detection, robust featureextraction, model compensation and adaptation, missing datatechniques and recognition of reverberant speech.
* Acts as a timely exposition of the topic in light of morewidespread use in the future of ASR technology in challengingenvironments.
* Addresses robustness issues and signal degradation which areboth key requirements for practitioners of ASR.
* Includes contributions from top ASR researchers from leadingresearch units in the field
Autoren-Porträt
Tuomas Virtanen, Tampere University of Technology, FinlandDr . Virtanen is a senior researcher at Tampere University of Technology. Previously, he has worked at Cambridge University, UK as a research associate. His main research contributions are in sound source separation and its application to robust speech recognition, audio content analysis, and music information retrieval. He is well-known for his work on non-negative matrix factorization based source separation, which is currently widely used in the field. He has published numerous journal and conference articles related to above topics.
Rita Singh, Carnegie Mellon University, USA
Dr. Singh is the CEO of a speech-technology startup but remains an adjunct faculty of the Language Technologies Institute at Carnegie Mellon University. She has been a major contributor to the open-source CMU sphinx and is one of the main architects of the popular Sphinx4 java-based open-source speech recognition system. In addition to her work on core speech recognition technology, she has also developed several algorithms for noise compensation, and was the prime architect of CMU's award-winning submission to the 2001 Naval Research Lab's challenge on automatic recognition of speech in noisy environments (SPINE).
Bhiksha Raj, Carnegie Mellon University, USA
Dr. Raj is an associate professor in the Language Technologies Institute and in Electrical and Computer Engineering at Carnegie Mellon University. He has worked extensively on robustness algorithms for speech recognition, and is very well-known for his contributions to the highly-popular VTS approach for noise compensation, as well as his contributions to missing-feature-based techniques for noise compensation. He has published extensively on and holds patents for algorithms for microphone array processing and signal separation.
Bibliographische Angaben
- 2012, 1. Auflage, 520 Seiten, Englisch
- Herausgegeben: Tuomas Virtanen, Rita Singh, Bhiksha Raj
- Verlag: John Wiley & Sons
- ISBN-10: 1118392671
- ISBN-13: 9781118392676
- Erscheinungsdatum: 19.09.2012
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 18 MB
- Mit Kopierschutz
Sprache:
Englisch
Kopierschutz
Dieses eBook können Sie uneingeschränkt auf allen Geräten der tolino Familie lesen. Zum Lesen auf sonstigen eReadern und am PC benötigen Sie eine Adobe ID.
Kommentar zu "Techniques for Noise Robustness in Automatic Speech Recognition"
0 Gebrauchte Artikel zu „Techniques for Noise Robustness in Automatic Speech Recognition“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Techniques for Noise Robustness in Automatic Speech Recognition".
Kommentar verfassen