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Illustrating the ways in which technological development grows out of government regulation, education innovation, professional profit-seeking, and social activism, this interdisciplinary study combines insights from several fields, among them the history of technology, human geography, mass communication, and information studies.

Speech-to-text systems. --- Speech processing systems

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Voiceprints. --- Speech perception. --- Speech, Intelligibility of.

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This revised and updated third edition describes the nature of sound, how sound is analyzed by the auditory system, and the rules and principles governing our interpretation of auditory input. It covers many topics including sound and the auditory system, locating sound sources, the basis for loudness judgments, perception of acoustic sequences, perceptual restoration of obliterated sounds, speech production and perception, and the relation of hearing to perception in general. Whilst keeping the consistent style of the previous editions, many new features have been added, including suggestions for further reading at the end of each chapter, a section on functional imaging of the brain, expanded information on pitch and infrapitch, and additional coverage of speech processing. Advanced undergraduate and graduate students interested in auditory perception, behavioral sciences, psychology, neurobiology, architectural acoustics, and the hearing sciences will find this book an excellent guide.

Auditory perception. --- Speech perception.

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Why Whisper? calls on Americans who believe in traditional values to resist the urge to stay silent and thus safe under the shameless onslaught of pressure, intimidation, and ridicule from the San Francisco-loving, NY Times reading, multicultural, anti-business, French-first, tree-hugging secular progressives and liberal political elites.

Freedom of speech --- United States.

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"In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-function form. In addition to all the necessary introduction of the background and tutorial material on the subject, we also included technical details on the derivation of the parameter optimization formulas for exponential-family distributions, discrete hidden Markov models (HMMs), and continuous-density HMMs in discriminative learning. Selected experimental results obtained by the authors in firsthand are presented to show that discriminative learning can lead to superior speech recognition performance over conventional parameter learning. Details on major algorithmic implementation issues with practical significance are provided to enable the practitioners to directly reproduce the theory in the earlier part of the book into engineering practice."--BOOK JACKET.

Automatic speech recognition --- Statistical methods.