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Embedded Architectures for Speech and Machine Learning: A Design Space Exploration Approach - Softcover
Synopsis
In recent years, research and development in the field of "natural interface" technologies and machine learning techniques have gained paramount importance. Text to Speech (TTS) conversion and Automated Speech Recognition (ASR) form a key part of such interface technologies. On the other hand, the future generation of intelligent computing devices will obviously require applications like machine learning based classifiers to perform classification tasks in a variety of fields ranging from data mining to recognition tasks in image and video. However, the real-time performance of such applications in hand-held platforms have not been explored till date. The present work takes into consideration some representative applications from these domains, evaluates their performance on embedded processor architectures and performs modifications in the underlying hardware platform for real time performance improvement of the concerned applications. The book can be used as supplementary text for advanced courses in embedded systems for demonstrating practical examples of key techniques like workload characterization, hardware-software co-design, custom instruction synthesis etc.
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About the Author
Soumyajit Dey did his B.Tech. in Electronics and Telecommunication Engg. from Jadavpur University, Kolkata, India in 2004 and MS (by research) in Computer Science and Engg. from Indian Institute of Technology (IIT), Kharagpur, India in 2007. Currently, he is working towards his Ph.D. at IIT Kharagpur.
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Embedded Architectures for Speech and Machine Learning
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LAP LAMBERT Academic Publishing Sep 2010, 2010
ISBN 10: 3838397304
ISBN 13: 9783838397306
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In recent years, research and development in the field of 'natural interface' technologies and machine learning techniques have gained paramount importance. Text to Speech (TTS) conversion and Automated Speech Recognition (ASR) form a key part of such interface technologies. On the other hand, the future generation of intelligent computing devices will obviously require applications like machine learning based classifiers to perform classification tasks in a variety of fields ranging from data mining to recognition tasks in image and video. However, the real-time performance of such applications in hand-held platforms have not been explored till date. The present work takes into consideration some representative applications from these domains, evaluates their performance on embedded processor architectures and performs modifications in the underlying hardware platform for real time performance improvement of the concerned applications. The book can be used as supplementary text for advanced courses in embedded systems for demonstrating practical examples of key techniques like workload characterization, hardware-software co-design, custom instruction synthesis etc. 128 pp. Englisch. Seller Inventory # 9783838397306
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Embedded Architectures for Speech and Machine Learning
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838397304
ISBN 13: 9783838397306
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dey SoumyajitSoumyajit Dey did his B.Tech. in Electronics and Telecommunication Engg. from Jadavpur University, Kolkata, India in 2004 and MS (by research) in Computer Science and Engg. from Indian Institute of Technology (IIT), Khar. Seller Inventory # 5419947
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Embedded Architectures for Speech and Machine Learning
Published by
LAP LAMBERT Academic Publishing Sep 2010, 2010
ISBN 10: 3838397304
ISBN 13: 9783838397306
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In recent years, research and development in the field of 'natural interface' technologies and machine learning techniques have gained paramount importance. Text to Speech (TTS) conversion and Automated Speech Recognition (ASR) form a key part of such interface technologies. On the other hand, the future generation of intelligent computing devices will obviously require applications like machine learning based classifiers to perform classification tasks in a variety of fields ranging from data mining to recognition tasks in image and video. However, the real-time performance of such applications in hand-held platforms have not been explored till date. The present work takes into consideration some representative applications from these domains, evaluates their performance on embedded processor architectures and performs modifications in the underlying hardware platform for real time performance improvement of the concerned applications. The book can be used as supplementary text for advanced courses in embedded systems for demonstrating practical examples of key techniques like workload characterization, hardware-software co-design, custom instruction synthesis etc.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch. Seller Inventory # 9783838397306
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Embedded Architectures for Speech and Machine Learning : A Design Space Exploration Approach
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LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838397304
ISBN 13: 9783838397306
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In recent years, research and development in the field of 'natural interface' technologies and machine learning techniques have gained paramount importance. Text to Speech (TTS) conversion and Automated Speech Recognition (ASR) form a key part of such interface technologies. On the other hand, the future generation of intelligent computing devices will obviously require applications like machine learning based classifiers to perform classification tasks in a variety of fields ranging from data mining to recognition tasks in image and video. However, the real-time performance of such applications in hand-held platforms have not been explored till date. The present work takes into consideration some representative applications from these domains, evaluates their performance on embedded processor architectures and performs modifications in the underlying hardware platform for real time performance improvement of the concerned applications. The book can be used as supplementary text for advanced courses in embedded systems for demonstrating practical examples of key techniques like workload characterization, hardware-software co-design, custom instruction synthesis etc. Seller Inventory # 9783838397306
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Embedded Architectures for Speech and Machine Learning: A Design Space Exploration Approach
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