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Performance Analysis Of An Automatic Speech Recognition System Augmented With Articulatory Features In Clean And Noisy Environments
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Book Synopsis Performance Analysis of an Automatic Speech Recognition System Augmented with Articulatory Features in Clean and Noisy Environments by : Praneeth Reddy Jannapu Reddy
Download or read book Performance Analysis of an Automatic Speech Recognition System Augmented with Articulatory Features in Clean and Noisy Environments written by Praneeth Reddy Jannapu Reddy and published by . This book was released on 2008 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Techniques for Noise Robustness in Automatic Speech Recognition by : Tuomas Virtanen
Download or read book Techniques for Noise Robustness in Automatic Speech Recognition written by Tuomas Virtanen and published by John Wiley & Sons. This book was released on 2012-11-28 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Speech Recognition by : France Mihelič
Download or read book Speech Recognition written by France Mihelič and published by BoD – Books on Demand. This book was released on 2008-11-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes.
Book Synopsis Distant Speech Recognition by : Matthias Woelfel
Download or read book Distant Speech Recognition written by Matthias Woelfel and published by John Wiley & Sons. This book was released on 2009-04-20 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete overview of distant automatic speech recognition The performance of conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon as the microphone is moved away from the mouth of the speaker. This is due to a broad variety of effects such as background noise, overlapping speech from other speakers, and reverberation. While traditional ASR systems underperform for speech captured with far-field sensors, there are a number of novel techniques within the recognition system as well as techniques developed in other areas of signal processing that can mitigate the deleterious effects of noise and reverberation, as well as separating speech from overlapping speakers. Distant Speech Recognitionpresents a contemporary and comprehensive description of both theoretic abstraction and practical issues inherent in the distant ASR problem. Key Features: Covers the entire topic of distant ASR and offers practical solutions to overcome the problems related to it Provides documentation and sample scripts to enable readers to construct state-of-the-art distant speech recognition systems Gives relevant background information in acoustics and filter techniques, Explains the extraction and enhancement of classification relevant speech features Describes maximum likelihood as well as discriminative parameter estimation, and maximum likelihood normalization techniques Discusses the use of multi-microphone configurations for speaker tracking and channel combination Presents several applications of the methods and technologies described in this book Accompanying website with open source software and tools to construct state-of-the-art distant speech recognition systems This reference will be an invaluable resource for researchers, developers, engineers and other professionals, as well as advanced students in speech technology, signal processing, acoustics, statistics and artificial intelligence fields.
Book Synopsis Robustness in Automatic Speech Recognition by : Jean-Claude Junqua
Download or read book Robustness in Automatic Speech Recognition written by Jean-Claude Junqua and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Automatic Speech Recognition on Vibrocervigraphic and Electromyographic Signals by : Szu-Chen Stan Jou
Download or read book Automatic Speech Recognition on Vibrocervigraphic and Electromyographic Signals written by Szu-Chen Stan Jou and published by . This book was released on 2008 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Automatic speech recognition (ASR) is a computerized speech-to-text process, in which speech is usually recorded with acoustical microphones by capturing air pressure changes. This kind of air-transmitted speech signal is prone to two kinds of problems related to noise robustness and applicability. The former means the mixing of speech signal and ambient noise usually deteriorates ASR performance. The latter means speech could be overheard easily on the air-transmission channel, and this often results in privacy loss or annoyance to other people. This thesis research solves these two problems by using channels that contact the human body without air transmission, i.e., by vibrocervigraphic and electromyographic methods. The vibrocervigraphic (VCG) method measures the throat vibration with a ceramic piezoelectric transducer contact to the skin on the neck, and the electromyographic (EMG) method measures the muscular electric potential with a set of electrodes attached to the skin where the articulatory muscles underlie. The VCG and EMG methods are inherently more robust to ambient noise, and they make it possible to recognize whispered and silent speech to improve applicability. The major contribution of this dissertation includes feature design and adaptation for optimizing features, acoustic model adaptation for adapting traditional acoustic models onto different feature spaces, and articulatory feature classification for incorporating articulatory information to improve recognition. For VCG ASR, the combination of feature transformation methods and maximum a posteriori adaptation improves the recognition accuracy even with a very small data set. On top of that, additive performance gain is achieved by applying maximum likelihood linear regression and feature space adaptation with different data granularities in order to adapt to channel variations as well as to speaker variations. For EMG ASR, we propose the Concise EMG feature that extracts representative EMG characteristics. It improves the recognition accuracy and advances the EMG ASR research from isolated word recognition to phone-based continuous speech recognition. Articulatory features are studied in both VCG and EMG ASR to analyze the systems and improve recognition accuracy. These techniques are demonstrated to be effective on both experimental evaluations and prototype applications."
Book Synopsis Acoustical and Environmental Robustness in Automatic Speech Recognition by : A. Acero
Download or read book Acoustical and Environmental Robustness in Automatic Speech Recognition written by A. Acero and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need for automatic speech recognition systems to be robust with respect to changes in their acoustical environment has become more widely appreciated in recent years, as more systems are finding their way into practical applications. Although the issue of environmental robustness has received only a small fraction of the attention devoted to speaker independence, even speech recognition systems that are designed to be speaker independent frequently perform very poorly when they are tested using a different type of microphone or acoustical environment from the one with which they were trained. The use of microphones other than a "close talking" headset also tends to severely degrade speech recognition -performance. Even in relatively quiet office environments, speech is degraded by additive noise from fans, slamming doors, and other conversations, as well as by the effects of unknown linear filtering arising reverberation from surface reflections in a room, or spectral shaping by microphones or the vocal tracts of individual speakers. Speech-recognition systems designed for long-distance telephone lines, or applications deployed in more adverse acoustical environments such as motor vehicles, factory floors, oroutdoors demand far greaterdegrees ofenvironmental robustness. There are several different ways of building acoustical robustness into speech recognition systems. Arrays of microphones can be used to develop a directionally-sensitive system that resists intelference from competing talkers and other noise sources that are spatially separated from the source of the desired speech signal.
Book Synopsis Automatic Speech Recognition on Mobile Devices and over Communication Networks by : Zheng-Hua Tan
Download or read book Automatic Speech Recognition on Mobile Devices and over Communication Networks written by Zheng-Hua Tan and published by Springer Science & Business Media. This book was released on 2008-04-17 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in computing and networking have sparked an enormous interest in deploying automatic speech recognition on mobile devices and over communication networks. This book brings together academic researchers and industrial practitioners to address the issues in this emerging realm and presents the reader with a comprehensive introduction to the subject of speech recognition in devices and networks. It covers network, distributed and embedded speech recognition systems.
Book Synopsis Invariant Features and Enhanced Speaker Normalization for Automatic Speech Recognition by : Florian Müller
Download or read book Invariant Features and Enhanced Speaker Normalization for Automatic Speech Recognition written by Florian Müller and published by Logos Verlag Berlin GmbH. This book was released on 2013 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic speech recognition systems have to handle various kinds of variabilities sufficiently well in order to achieve high recognition rates in practice. One of the variabilities that has a major impact on the performance is the vocal tract length of the speakers. Normalization of the features and adaptation of the acoustic models are commonly used methods in speech recognition systems. In contrast to that, a third approach follows the idea of extracting features with transforms that are invariant to vocal tract lengths changes. This work presents several approaches for extracting invariant features for automatic speech recognition systems. The robustness of these features under various training-test conditions is evaluated and it is described how the robustness of the features to noise can be increased. Furthermore, it is shown how the spectral effects due to different vocal tract lengths can be estimated with a registration method and how this can be used for speaker normalization.
Book Synopsis Automatic Speech Recognition System Performance Analysis Using a Visual Lingual Feedback Model by : Ricky E. Wells
Download or read book Automatic Speech Recognition System Performance Analysis Using a Visual Lingual Feedback Model written by Ricky E. Wells and published by . This book was released on 1999 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Speech Recognition of Uncertain or Missing Data by : Dorothea Kolossa
Download or read book Robust Speech Recognition of Uncertain or Missing Data written by Dorothea Kolossa and published by Springer Science & Business Media. This book was released on 2011-07-14 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Speech Recognition Using Articulatory and Excitation Source Features by : K. Sreenivasa Rao
Download or read book Speech Recognition Using Articulatory and Excitation Source Features written by K. Sreenivasa Rao and published by Springer. This book was released on 2017-01-11 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.
Book Synopsis Speechreading by Humans and Machines by : David G. Stork
Download or read book Speechreading by Humans and Machines written by David G. Stork and published by Springer Science & Business Media. This book was released on 1996-09-01 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is one outcome of the NATO Advanced Studies Institute (ASI) Workshop, "Speechreading by Man and Machine," held at the Chateau de Bonas, Castera-Verduzan (near Auch, France) from August 28 to Septem ber 8, 1995 - the first interdisciplinary meeting devoted the subject of speechreading ("lipreading"). The forty-five attendees from twelve countries covered the gamut of speechreading research, from brain scans of humans processing bi-modal stimuli, to psychophysical experiments and illusions, to statistics of comprehension by the normal and deaf communities, to models of human perception, to computer vision and learning algorithms and hardware for automated speechreading machines. The first week focussed on speechreading by humans, the second week by machines, a general organization that is preserved in this volume. After the in evitable difficulties in clarifying language and terminology across disciplines as diverse as human neurophysiology, audiology, psychology, electrical en gineering, mathematics, and computer science, the participants engaged in lively discussion and debate. We think it is fair to say that there was an atmosphere of excitement and optimism for a field that is both fascinating and potentially lucrative. Of the many general results that can be taken from the workshop, two of the key ones are these: • The ways in which humans employ visual image for speech recogni tion are manifold and complex, and depend upon the talker-perceiver pair, severity and age of onset of any hearing loss, whether the topic of conversation is known or unknown, the level of noise, and so forth.
Book Synopsis Impact of Noise in Automatic Speech Recognition for Low-resourced Languages by : Vigneshwar Lakshminarayanan
Download or read book Impact of Noise in Automatic Speech Recognition for Low-resourced Languages written by Vigneshwar Lakshminarayanan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The usage of deep learning algorithms has resulted in significant progress in automatic speech recognition (ASR). The ASR models may require over a thousand hours of speech data to accurately recognize the speech. There have been case studies that have indicated that there are certain factors like noise, acoustic distorting conditions, and voice quality that has affected the performance of speech recognition. In this research, we investigate the impact of noise on Automatic Speech Recognition and explore novel methods for developing noise-robust ASR models using the Tamil language dataset with limited resources. We are using the speech dataset provided by SpeechOcean.com and Microsoft for the Indian languages. We add several kinds of noise to the dataset and find out how these noises impact the ASR performance. We also determine whether certain data augmentation methods like raw data augmentation and spectrogram augmentation (SpecAugment) are better suited to different types of noises. Our results show that all noises, regardless of the type, had an impact on ASR performance, and upgrading the architecture alone were unable to mitigate the impact of noise. Raw data augmentation enhances ASR performance on both clean data and noise-mixed data, however, this was not the case with SpecAugment on the same test sets. As a result, raw data augmentation performs way better than SpecAugment over the baseline models."--Abstract.
Book Synopsis Robust Automatic Speech Recognition by : Jinyu Li
Download or read book Robust Automatic Speech Recognition written by Jinyu Li and published by Academic Press. This book was released on 2015-10-30 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Modern Speech Recognition by : S. Ramakrishnan
Download or read book Modern Speech Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2012-11-28 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses primarily on speech recognition and the related tasks such as speech enhancement and modeling. This book comprises 3 sections and thirteen chapters written by eminent researchers from USA, Brazil, Australia, Saudi Arabia, Japan, Ireland, Taiwan, Mexico, Slovakia and India. Section 1 on speech recognition consists of seven chapters. Sections 2 and 3 on speech enhancement and speech modeling have three chapters each respectively to supplement section 1. We sincerely believe that thorough reading of these thirteen chapters will provide comprehensive knowledge on modern speech recognition approaches to the readers.
Book Synopsis New Era for Robust Speech Recognition by : Shinji Watanabe
Download or read book New Era for Robust Speech Recognition written by Shinji Watanabe and published by Springer. This book was released on 2017-10-30 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
