Author: Hans-Peter Hutter
Publisher: vdf Hochschulverlag AG
ISBN: 9783728124241
Category : Technology & Engineering
Languages : en
Pages : 244
Book Description
Comparison of Classic and Hybrid HMM Approaches to Speech Recognition Over Telephone Lines
Author: Hans-Peter Hutter
Publisher: vdf Hochschulverlag AG
ISBN: 9783728124241
Category : Technology & Engineering
Languages : en
Pages : 244
Book Description
Publisher: vdf Hochschulverlag AG
ISBN: 9783728124241
Category : Technology & Engineering
Languages : en
Pages : 244
Book Description
Proceedings
Author:
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 542
Book Description
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 542
Book Description
Connectionist Speech Recognition
Author: Hervé A. Bourlard
Publisher: Springer Science & Business Media
ISBN: 9780792393962
Category : Computers
Languages : en
Pages : 358
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.
Publisher: Springer Science & Business Media
ISBN: 9780792393962
Category : Computers
Languages : en
Pages : 358
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.
International Books in Print
Author:
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 1294
Book Description
Publisher:
ISBN:
Category : English imprints
Languages : en
Pages : 1294
Book Description
Robust Automatic Speech Recognition
Author: Jinyu Li
Publisher: Academic Press
ISBN: 0128026162
Category : Technology & Engineering
Languages : en
Pages : 308
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
Publisher: Academic Press
ISBN: 0128026162
Category : Technology & Engineering
Languages : en
Pages : 308
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
Electrical & Electronics Abstracts
Author:
Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 1860
Book Description
Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 1860
Book Description
Fundamentals of Speech Recognition
Author: Lawrence R. Rabiner
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
Book Description
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
Book Description
Spoken Language Understanding
Author: Gokhan Tur
Publisher: John Wiley & Sons
ISBN: 1119993946
Category : Language Arts & Disciplines
Languages : en
Pages : 443
Book Description
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.
Publisher: John Wiley & Sons
ISBN: 1119993946
Category : Language Arts & Disciplines
Languages : en
Pages : 443
Book Description
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.
Introduction to Digital Speech Processing
Author: Lawrence R. Rabiner
Publisher: Now Publishers Inc
ISBN: 1601980701
Category : Computers
Languages : en
Pages : 212
Book Description
Provides the reader with a practical introduction to the wide range of important concepts that comprise the field of digital speech processing. Students of speech research and researchers working in the field can use this as a reference guide.
Publisher: Now Publishers Inc
ISBN: 1601980701
Category : Computers
Languages : en
Pages : 212
Book Description
Provides the reader with a practical introduction to the wide range of important concepts that comprise the field of digital speech processing. Students of speech research and researchers working in the field can use this as a reference guide.
Speech and Computer
Author: Andrey Ronzhin
Publisher: Springer
ISBN: 3319439588
Category : Computers
Languages : en
Pages : 747
Book Description
This book constitutes the proceedings of the 18th International Conference on Speech and Computer, SPECOM 2016, held in Budapest, Hungary, in August 2016. The 85 papers presented in this volume were carefully reviewed and selected from 154 submissions.
Publisher: Springer
ISBN: 3319439588
Category : Computers
Languages : en
Pages : 747
Book Description
This book constitutes the proceedings of the 18th International Conference on Speech and Computer, SPECOM 2016, held in Budapest, Hungary, in August 2016. The 85 papers presented in this volume were carefully reviewed and selected from 154 submissions.