The remarkable advances in computing and networking have sparked an enormous interest in deploying automatic speech recognition on mobile devices and over communication networks. This trend is accelerating.
This book brings together leading 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, which are expected to co-exist in the future. It offers a wide-ranging, unified approach to the topic and its latest development, also covering the most up-to-date standards and several off-the-shelf systems.
• Provides an in-depth review of network speech recognition, distributed speech recognition, embedded speech recognition, systems and applications
• Begins with a comprehensive overview of the subject, discussing the pros and cons of the presented approaches, and guiding the reader through the following chapters
• Includes platforms like mobile phones, PDAs and automobiles
• Presents state-of-the-art methods, advanced systems, and the latest standards
• Offers working knowledge needed for both research and practice
• References supplemental material at associated complementary website at: http://asr.es.aau.dk
This all-inclusive text/reference is an essential read for graduate students, scientists and engineers working or researching in the field of speech recognition and processing. It offers a self-contained approach to this hot research topic.
|Series:||Advances in Computer Vision and Pattern Recognition Series|
|Product dimensions:||6.10(w) x 9.25(h) x 0.24(d)|
Table of Contents
Networked, Distributed and Embedded Speech Recognition: An Overview.- Speech Coding and Packet Loss Effects on Speech and Speaker.- Speech Recognition over Mobile Networks.- Speech Recognition over IP Networks.- Distributed Speech Recognition Standards.- Speech Feature Extraction and Reconstruction.- Quantization of Speech Features: Source Coding.- Error Recovery: Channel Coding and Packetization.- Error Concealment.- Algorithm Optimizations: Low Computational Complexity.- Algorithm Optimizations: Low Memory Footprint.- Fixed-point Arithmetic.- Software Architectures for Networked Mobile Speech Applications.- Speech Recognition in Mobile Phones.- Handheld Speech to Speech Translation System.- Automotive Speech Recognition.- Energy-aware Speech Recognition for Mobile Devices.