Artificial Bandwidth Extension of Telephone Speech Signals Using Phonetic A Priori Knowledge PDF Download

Author: Patrick Marcel Bauer
Publisher:
ISBN: 9783844050721
Category :
Languages : en
Pages :

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Author: Bernd Iser
Publisher: Springer
ISBN: 9780387564852
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
Bandwidth Extension of Speech Signals describes the theory and methods for quality enhancement of clean speech signals and distorted speech signals such as those that have undergone a band limitation, for instance, in a telephone network. Problems and the respective solutions are discussed for the different approaches. The different approaches are evaluated and a real-time implementation of the most promising approach is presented. The book includes topics related to speech coding, pattern- / speech recognition, speech enhancement, statistics and digital signal processing in general.

Author: Bernd Iser
Publisher: Springer
ISBN: 9781441943361
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
Bandwidth Extension of Speech Signals describes the theory and methods for quality enhancement of clean speech signals and distorted speech signals such as those that have undergone a band limitation, for instance, in a telephone network. Problems and the respective solutions are discussed for the different approaches. The different approaches are evaluated and a real-time implementation of the most promising approach is presented. The book includes topics related to speech coding, pattern- / speech recognition, speech enhancement, statistics and digital signal processing in general.

Author: Hervé A. Bourlard
Publisher: Springer Science & Business Media
ISBN: 1461532108
Category : Technology & Engineering
Languages : en
Pages : 329

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Book Description
Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

Author: Mark Gales
Publisher: Now Publishers Inc
ISBN: 1601981201
Category : Automatic speech recognition
Languages : en
Pages : 125

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Book Description
The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.

Author: Jinyu Li
Publisher: Academic Press
ISBN: 0128026162
Category : Technology & Engineering
Languages : en
Pages : 308

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Book Description
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: Joseph Keshet
Publisher: John Wiley & Sons
ISBN: 9780470742037
Category : Technology & Engineering
Languages : en
Pages : 268

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Book Description
This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.

Author: João Freitas
Publisher: Springer
ISBN: 9783319401737
Category : Technology & Engineering
Languages : en
Pages : 0

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Book Description
This book provides a broad and comprehensive overview of the existing technical approaches in the area of silent speech interfaces (SSI), both in theory and in application. Each technique is described in the context of the human speech production process, allowing the reader to clearly understand the principles behind SSI in general and across different methods. Additionally, the book explores the combined use of different data sources, collected from various sensors, in order to tackle the limitations of simpler SSI approaches, addressing current challenges of this field. The book also provides information about existing SSI applications, resources and a simple tutorial on how to build an SSI.

Author: Xuedong Huang
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 1018

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Book Description
Remarkable progress is being made in spoken language processing, but many powerful techniques have remained hidden in conference proceedings and academic papers, inaccessible to most practitioners. In this book, the leaders of the Speech Technology Group at Microsoft Research share these advances -- presenting not just the latest theory, but practical techniques for building commercially viable products.KEY TOPICS: Spoken Language Processing draws upon the latest advances and techniques from multiple fields: acoustics, phonology, phonetics, linguistics, semantics, pragmatics, computer science, electrical engineering, mathematics, syntax, psychology, and beyond. The book begins by presenting essential background on speech production and perception, probability and information theory, and pattern recognition. The authors demonstrate how to extract useful information from the speech signal; then present a variety of contemporary speech recognition techniques, including hidden Markov models, acoustic and language modeling, and techniques for improving resistance to environmental noise. Coverage includes decoders, search algorithms, large vocabulary speech recognition techniques, text-to-speech, spoken language dialog management, user interfaces, and interaction with non-speech interface modalities. The authors also present detailed case studies based on Microsoft's advanced prototypes, including the Whisper speech recognizer, Whistler text-to-speech system, and MiPad handheld computer.MARKET: For anyone involved with planning, designing, building, or purchasing spoken language technology.

Author: Jonathan Harrington
Publisher: John Wiley & Sons
ISBN: 1405141697
Category : Language Arts & Disciplines
Languages : en
Pages : 468

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Book Description
An accessible introduction to the phonetic analysis of speech corpora, this workbook-style text provides an extensive set of exercises to help readers develop the necessary skills to design and carry out experiments in speech research. Offers the first step-by-step treatment of advanced techniques in experimental phonetics using speech corpora and downloadable software, including the R programming language Introduces methods of analyzing phonetically-labelled speech corpora, with the goal of testing hypotheses that often arise in experimental phonetics and laboratory phonology Incorporates an extensive set of exercises and answers to reinforce the techniques introduced Accessibly written with easy-to-follow computer commands and spectrograms of speech Companion website at www.wiley.com/go/harrington, which includes illustrations, video tutorials, appendices, and downloadable speech corpora for testing purposes. Discusses techniques in digital speech processing and in structuring and querying annotations from speech corpora Includes substantial coverage of analysis, including measuring gestural synchronization using EMA, the acoustics of vowels, consonant overlap using EPG, spectral analysis of fricatives and obstruents, and the probabilistic classification of acoustic speech data