Recent Advances In Robust Speech Recognition Technology PDF Download
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| Author | : Hirokazu Tohya |
| Publisher | : |
| Total Pages | : |
| Release | : 2011-02-10 |
| Genre | : |
| ISBN | : 9781608053896 |
Download Recent Advances in Robust Speech Recognition Technology Book in PDF, ePub and Kindle
"This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or whe"
| Author | : Javier Ramirez |
| Publisher | : Bentham Science |
| Total Pages | : 223 |
| Release | : 2011 |
| Genre | : Computers |
| ISBN | : 1608051722 |
Download Recent Advances in Robust Speech Recognition Technology Book in PDF, ePub and Kindle
"This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or whe"
| Author | : Jean-Claude Junqua |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 457 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1461312973 |
Download Robustness in Automatic Speech Recognition Book in PDF, ePub and Kindle
Foreword Looking back the past 30 years. we have seen steady progress made in the area of speech science and technology. I still remember the excitement in the late seventies when Texas Instruments came up with a toy named "Speak-and-Spell" which was based on a VLSI chip containing the state-of-the-art linear prediction synthesizer. This caused a speech technology fever among the electronics industry. Particularly. applications of automatic speech recognition were rigorously attempt ed by many companies. some of which were start-ups founded just for this purpose. Unfortunately. it did not take long before they realized that automatic speech rec ognition technology was not mature enough to satisfy the need of customers. The fever gradually faded away. In the meantime. constant efforts have been made by many researchers and engi neers to improve the automatic speech recognition technology. Hardware capabilities have advanced impressively since that time. In the past few years. we have been witnessing and experiencing the advent of the "Information Revolution." What might be called the second surge of interest to com mercialize speech technology as a natural interface for man-machine communication began in much better shape than the first one. With computers much more powerful and faster. many applications look realistic this time. However. there are still tremendous practical issues to be overcome in order for speech to be truly the most natural interface between humans and machines.
| Author | : Jinyu Li |
| Publisher | : Academic Press |
| Total Pages | : 308 |
| Release | : 2015-10-30 |
| Genre | : Technology & Engineering |
| ISBN | : 0128026162 |
Download Robust Automatic Speech Recognition Book 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
| Author | : Antonio Peinado |
| Publisher | : John Wiley & Sons |
| Total Pages | : 274 |
| Release | : 2006-08-04 |
| Genre | : Technology & Engineering |
| ISBN | : 0470024011 |
Download Speech Recognition Over Digital Channels Book in PDF, ePub and Kindle
Automatic speech recognition (ASR) is a very attractive means for human-machine interaction. The degree of maturity reached by speech recognition technologies during recent years allows the development of applications that use them. In particular, ASR shows an enormous potential in mobile environments, where devices such as mobile phones or PDAs are used, and for Internet Protocol (IP) applications. Speech Recognition Over Digital Channels is the first book of its kind to offer a complete system comprehension, addressing the topics of distributed and network-based speech recognition issues and standards, the concepts of speech processing and transmission, and system architectures and robustness. Describes the different client/server architectures for remote speech recognition systems, by means of which the client transmits speech parameters through a digital channel to a remote recognition server Focuses on robustness against both adverse acoustic environments (in the front-end) and bit errors/packet loss Discusses four ETSI standards for distributed speech recognition; the understanding of the standards and the technologies behind them Provides the necessary background for the comprehension of remote speech recognition technologies This book will appeal to a wide-ranging audience: engineers using speech recognition systems, researchers involved in ASR systems and those interested in processing and transmitting speech such as signal processing and communications communities. It will also be of interest to technical experts requiring an understanding of recognition over mobile and IP networks, and postgraduate students working on robust speech processing.
| Author | : Shinji Watanabe |
| Publisher | : Springer |
| Total Pages | : 436 |
| Release | : 2017-10-30 |
| Genre | : Computers |
| ISBN | : 331964680X |
Download New Era for Robust Speech Recognition Book in PDF, ePub and Kindle
This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.
| Author | : Michael Grimm |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 471 |
| Release | : 2007-06-01 |
| Genre | : Computers |
| ISBN | : 3902613084 |
Download Robust Speech Book in PDF, ePub and Kindle
This book on Robust Speech Recognition and Understanding brings together many different aspects of the current research on automatic speech recognition and language understanding. The first four chapters address the task of voice activity detection which is considered an important issue for all speech recognition systems. The next chapters give several extensions to state-of-the-art HMM methods. Furthermore, a number of chapters particularly address the task of robust ASR under noisy conditions. Two chapters on the automatic recognition of a speaker's emotional state highlight the importance of natural speech understanding and interpretation in voice-driven systems. The last chapters of the book address the application of conversational systems on robots, as well as the autonomous acquisition of vocalization skills.
| Author | : Dorothea Kolossa |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 387 |
| Release | : 2011-07-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3642213170 |
Download Robust Speech Recognition of Uncertain or Missing Data Book in PDF, ePub and Kindle
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
| Author | : Thomas Fang Zheng |
| Publisher | : Springer |
| Total Pages | : 49 |
| Release | : 2017-04-06 |
| Genre | : Technology & Engineering |
| ISBN | : 9811032386 |
Download Robustness-Related Issues in Speaker Recognition Book in PDF, ePub and Kindle
This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.
| Author | : J.M. Gorriz |
| Publisher | : |
| Total Pages | : |
| Release | : 2007 |
| Genre | : |
| ISBN | : 9783902613080 |
Download New Advances in Voice Activity Detection Using HOS and Optimization Strategies Book in PDF, ePub and Kindle
This paper showed three different schemes for improving speech detection robustness and the performance of speech recognition systems working in noisy environments. These methods are based on: i) statistical likelihood ratio tests (LRTs) formulated in terms of the integrated bispectrum of the noisy signal. The integrated bispectrum is defined as a cross spectrum between the signal and its square, and therefore a function of a single frequency variable. It inherits the ability of higher order statistics to detect signals in noise with many other additional advantages; ii) Hard decision clustering approach where a set of prototypes is used to characterize the noisy channel. Detecting the presence of speech is enabled by a decision rule formulated in terms of an averaged distance between the observation vector and a cluster-based noise model; and iii) an effective method employing support vector machines (SVM) , a paradigm of learning from examples based in Vapkik-Chervonenkis theory. The use of kernels in SVM enables to map the data, via a nonlinear transformation, into some other dot product space (called feature space) in which the classification task is settled. The proposed methods incorporate contextual information to the decision rule, a strategy that has reported significant improvements in speech detection accuracy and robust speech recognition applications. The optimal window size was determined by analyzing the overlap between the distributions of the decision variable and the error rate. The experimental analysis conducted on the well-known AURORA databases has reported significant improvements over standardized techniques such as ITU G.729, AMR1, AMR2 and ESTI AFE VADs, as well as over recently published VADs. The analysis assessed: i) the speech/non-speech detection accuracy by means of the ROC curves, with the proposed VADs yielding improved hit-rates and reduced false alarms when compared to all the reference algorithms, and ii) the recognition rate when the VADs are considered as part of a complete speech recognition system, showing a sustained advantage in speech recognition performance.
