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This comprehensive book ties strong academic foundations directly to their clinical application for speech/language therapists working with speech sound disorders. Each chapter presents tools to help readers bridge the gap between theoretical issues and clinical applications by presenting Clinical Applications, Clinical Exercises, Case Studies, and a section called Think Critically, which asks students to further apply specific clinical concepts. Test Yourself multiple choice questions appear at the end of each chapter and are ideal for review and assessment of the knowledge presented in the chapters, and Further Readings allow readers to continue to expand their knowledge.
The new Fifth Edition of Articulation and Phonology in Speech Sound Disordersreflects the current use of the term "speech sound disorder," an umbrella term for what was previously noted as articulation- and phonemic-based disorders. Also included is an in-depth review of the phonotactics of American English; increased focus on topics which have gained recognition with the field; an expanded chapter on the Treatment of Phonemic-Based Speech Sound Disorders (Chapter 10); an updated chapter on Speech Sound Disorders in Selected populations; and the addition of several videos in the Enhanced Pearson eText which support the content of the chapter and allow more clinical and transcription exercise for students.
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0134092627 / 9780134092621 Articulation and Phonology in Speech Sound Disorders with Enhanced Pearson eText -- Access Card Package, 5/e
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This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.
God is infinite, but language finite; thus speech would seem to condemn Him to finitude. In speaking of God, would the theologian violate divine transcendence by reducing God to immanence, or choose, rather, to remain silent? At stake in this argument is a core problem of the conditions of divine revelation. How, in terms of language and the limitations of human understanding, can transcendence ever be made known? Does its very appearance not undermine its transcendence, its condition of unknowability?
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