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Network Speech Recognition.- Network, Distributed and Embedded Speech Recognition: An Overview.- Speech Coding and Packet Loss Effects on Speech and Speaker Recognition.- Speech Recognition Over Mobile Networks.- Speech Recognition Over IP Networks.- Distributed Speech Recognition.- Distributed Speech Recognition Standards.- Speech Feature Extraction and Reconstruction.- Quantization of Speech Features: Source Coding.- Error Recovery: Channel Coding and Packetization.- Error Concealment.- Embedded Speech Recognition.- Algorithm Optimizations: Low Computational Complexity.- Algorithm Optimizations: Low Memory Footprint.- Fixed-Point Arithmetic.- Systems and Applications.- 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. • ISBN:9781848001428 • Format:Hardcover • Publication Date:2008-03-20
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Source coding refers to the process of encoding information using fewer bits compared to the original data. It can be lossy or lossless. Lossless compression is characterized by the elimination of loss of information and statistical redundancy. In lossy compression, bits are reduced by removing unnecessary information. In both these compressions, using the techniques of linear prediction, coding and pattern recognition, there is a reduction in information redundancy. Such compression of data is useful for storing and transmission of data. Some of the video coding formats are MPEG-2 Part 2, MPEG-4 Part 2, AV1, Theora, etc. Some vastly popular and commonly used image coding formats are JPEG, PNG and GIF. This book traces the progress in the field of image and video coding and highlights some of its key concepts. It includes some of the vital pieces of work being conducted across the world, on various topics related to coding standards, tools and techniques. It is a resource guide for experts as well as students. Source coding refers to the process of encoding information using fewer bits compared to the original data. It can be lossy or lossless. Lossless compression is characterized by the elimination of loss of information and statistical redundancy. In lossy compression, bits are reduced by removing unnecessary information. In both these compressions, using the techniques of linear prediction, coding and pattern recognition, there is a reduction in information redundancy. Such compression of data is useful for storing and transmission of data. Some of the video coding formats are MPEG-2 Part 2, MPEG-4 Part 2, AV1, Theora, etc. Some vastly popular and commonly used image coding format
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