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e-book Robustness in Automatic Speech Recognition: Fundamentals and Applications

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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 Naval Research Lab's challenge on automatic recognition of speech in noisy environments SPINE.

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.

Robust Automatic Speech Recognition [Book]

He has published extensively on and holds patents for algorithms for microphone array processing and signal separation. Permissions Request permission to reuse content from this site. Stern, Nelson Morgan. Hershey, Steven J. Rennie, Jonathan Le Roux. Undetected location. NO YES. Selected type: E-Book. Added to Your Shopping Cart.


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View on Wiley Online Library. This is a dummy description. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech.

Fundamentals and Applications

Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Author Junqua, Jean-claude. Physical Description xxx, p.

Robustness in Automatic Speech Recognition: Fundamentals and Applications

VLSI, computer architecture and digital signal processing Kluwer international series in engineering and computer science. Subjects Automatic speech recognition. Signal processing.

Contents Pt. Speech Communication by Humans and Machines. Nature and Perception of Speech Sounds. Background on Speech Analysis.

Fundamentals of Automatic Speech Recognition Pt. Speaker Variability and Specificity.


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Possible Solutions and Some Perspectives. Towards Robust Speech Analysis. On the Use of a Robust Speech Representation. Word-Spotting and Rejection. Spontaneous Speech.

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Application Domain, Human Factors, and Dialogue. Notes Includes bibliographical references and index. View online Borrow Buy Freely available Show 0 more links Set up My libraries How do I set up "My libraries"? University of Queensland Library. Open to the public ; TK None of your libraries hold this item.