Robust Speaker Recognition in Noisy Environments - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robust Speaker Recognition in Noisy Environments write by K. Sreenivasa Rao. This book was released on 2014-06-21. Robust Speaker Recognition in Noisy Environments available in PDF, EPUB and Kindle. This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.
Techniques for Noise Robustness in Automatic Speech Recognition
Techniques for Noise Robustness in Automatic Speech Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Techniques for Noise Robustness in Automatic Speech Recognition write by Tuomas Virtanen. This book was released on 2012-11-28. Techniques for Noise Robustness in Automatic Speech Recognition available in PDF, EPUB and Kindle. Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. 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. 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. Includes contributions from top ASR researchers from leading research units in the field
Robust Speech Recognition Under Noisy Environments
Robust Speech Recognition Under Noisy Environments - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robust Speech Recognition Under Noisy Environments write by Siu Wa Lee. This book was released on 2004. Robust Speech Recognition Under Noisy Environments available in PDF, EPUB and Kindle.
Robust Automatic Speech Recognition
Robust Automatic Speech Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Robust Automatic Speech Recognition write by Jinyu Li. This book was released on 2015-10-30. Robust Automatic Speech Recognition available in PDF, EPUB and Kindle. 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 The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years
Speech Processing in Mobile Environments
Speech Processing in Mobile Environments - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Speech Processing in Mobile Environments write by K. Sreenivasa Rao. This book was released on 2014-01-28. Speech Processing in Mobile Environments available in PDF, EPUB and Kindle. This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. The methods presented in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments. The authors provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral enhancement methods to minimize the effect of noise and examining methods and models on speech and speaker recognition applications in mobile environments.
