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Fundamentals of speech recognition Juang B. H., Rabiner L.
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Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. Besides, the two fundamental parts, LPS and Newton's method, both contribute to the excellent performance of the proposed algorithm. The main objective of speech recognition is to get a higher recognition rate. Claudio Becchetti, Prina Ricotti. However, lots of factors tend to degrade the performance of automatic speech recognition (ASR) system, such as environmental noise, channel distortion, and speaker variability [1, 2]. Download Savoring France: Reci Download Complex Issues in Chi preview. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models. Fundamentals of Speech Recognition ebook downloads. Fundamentals of Speech Recognition (Prentice Hall Signal Processing Series) Lawrence Rabiner, Biing-Hwang Juan Prentice Hall PTR 1993. Best Speech Recognition Books Fundamentals of Speech Recognition. Speech Recognition Books Speech Recognition: Theory and C++ Implementation.