Data-Driven Techniques in Speech Synthesis / Edition 1

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This first review of a new field covers all areas of speech synthesis from text, ranging from text analysis to letter-to-sound conversion. At the leading edge of current research, the concise and accessible book is written by well respected experts in the field.

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Table of Contents

1. Learning About Speech from Data: Beyond NETtalk; R.I. Damper. 2. Constructing High-Accuracy Letter-to-Phoneme Rules with Machine Learning; G. Bakiri, Th.G. Dietterich. 3. Analogy, the Corpus and Pronunciation; K.P.H. Sullivan. 4. A Hierarchical Lexical Representation for Pronunciation Generation; H. Meng. 5. English Letter-Phoneme Conversion by Stochastic Transducers; R.W.P. Luk, R.I. Damper. 6. Selection of Multiphone Synthesis Units and Grapheme-to-Phoneme Transcription using Variable-Length Modeling of Strings; S. Deligne, et al. 7. TREETALK: Memory-Based Word Phonemisation; W. Daelemans, A. van den Bosch. 8. Learnable Phonetic Representations in a Connectionist TTS System - I: Text to Phonetics; A.D. Cohen. 9. Using the Tilt Intonation Model: A Data-Driven Approach; A.W. Black, et al. 10. Estimation of Parameters for the Klatt Synthesizer from a Speech Database; J. Coleman, A. Slater. 11. Training Accent and Phrasing Assignment on Large Corpora; J. Hirschberg. 12. Learnable Phonetic Representations in a Connectionist TTS System - II: Phonetics to Speech; A.D. Cohen.
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