Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
This book is a comprehensive guide on building systems that interact with the user via speech as well as other modalities. The fundamentals of speech recognition, text -to-speech and dialog processing will be discussed as components present in a Spoken Language System. The book will be structured in two parts, with the first part including the principles of the basic disciplines needed, and the second part explaining the different speech technologies. This is the definitive book on spoken language systems written by the people at Microsoft Research who have developed the voice-activated technologies that will be imbedded in Windows 2000 and other key Microsoft products of the future. This is not a Microsoft book, however, this is a book on the science and linguistics of this technology and how to use it in developing and building hardware and software products.
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Acoustics algorithm analysis approximation Audio autocorrelation Bayes beam search bigram cepstrum Chapter classifier codebook coding coefficients complex compute Conf consonants convergence covariance matrix data samples decision decoding defined denote described digital signal entropy Equation error rate example filter formant Fourier transform frequency Gaussian distribution given grammar Hidden Markov Models IEEE Int IEEE Trans input language model linear low-pass filter MAP estimation mean method microphone minimize n-gram node noise observed obtained output parameters path pattern recognition phonetic pitch period posterior posterior probability prediction probability Proc pruning quantization random variable Section segment semantic sentence sequence shown in Figure Signal Processing sound speaker spectral Speech and Signal speech recognition systems speech signal speech synthesis spoken language processing squared error statistical techniques theory tion training data tree typically variance vector Viterbi Viterbi search voiced vowel waveform window word z-transform
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Mustererkennung Mit Markov-Modellen: Theorie - Praxis - Anwendungsgebiete
Gernot A. Fink
No preview available - 2003