Description: Robust Automatic Speech Recognition A Bridge to Practical Applications Learn how automatic speech recognition can be used with robustness in real-world applications Jinyu Li (Author), Li Deng (Author), Reinhold Haeb-Umbach (Author), Yifan Gong (Author) 9780128023983, Elsevier Science Hardback, published 14 October 2015 306 pages 23.5 x 19 x 2.3 cm, 0.79 kg Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications.The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided.The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition Learn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology development Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition Introduction Fundamental of speech recognition Background of robust speech recognition Processing in the Feature and Model Domains Compensation with prior knowledge Explicit distortion modeling Uncertainty processing Joint model training Reverberant speech recognition Multi-channel processing Summary and Future Directions Subject Areas: Acoustic & sound engineering [TTA], Electronics & communications engineering [TJ], Mechanical engineering [TGB]
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BIC Subject Area 1: Acoustic & sound engineering [TTA]
BIC Subject Area 2: Electronics & communications engineering [TJ]
BIC Subject Area 3: Mechanical engineering [TGB]
Subject Area: Mechanical Engineering
Item Height: 235 mm
Item Width: 191 mm
Author: Reinhold Hab-Umbach, Jinyu Li, Yifan Gong, Li Deng
Publication Name: Robust Automatic Speech Recognition: a Bridge to Practical Applications
Format: Hardcover
Language: English
Publisher: Elsevier Science Publishing Co INC International Concepts
Subject: Engineering & Technology, Computer Science
Publication Year: 2015
Type: Textbook
Item Weight: 790 g
Number of Pages: 306 Pages