Predicting Prosody from Text for Text-to-Speech Synthesis - libro nuevo

EAN (ISBN-13): 9781461413387
ISBN (ISBN-10): 1461413389
Año de publicación: 2012
Editorial: Springer New York

Libro en la base de datos desde 2007-09-26T05:37:07-05:00 (Mexico City)
Página de detalles modificada por última vez el 2023-06-09T09:59:10-06:00 (Mexico City)
ISBN/EAN: 9781461413387

ISBN - escritura alterna:
1-4614-1338-9, 978-1-4614-1338-7
Mode alterno de escritura y términos de búsqueda relacionados:
Autor del libro: rao
Título del libro: synthesis

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Datos del la editorial

Autor: K. Sreenivasa Rao
Título: SpringerBriefs in Speech Technology; Predicting Prosody from Text for Text-to-Speech Synthesis
Editorial: Springer; Springer US
130 Páginas
Año de publicación: 2012-04-27
New York; NY; US
Idioma: Inglés
53,49 € (DE)
55,00 € (AT)
59,00 CHF (CH)
Available
XII, 130 p. 42 illus.

EA; E107; eBook; Nonbooks, PBS / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Elektronik; Verstehen; Duration; Epochs; Glottal closure instants; Intonation; Linguistic constraints; Neural networks; Non-linear models; Pitch; Production constraints; Prosody; Prosody modification; Support vector machines; Text-to-speech synthesis; Time scale modification; C; Signal, Speech and Image Processing; Computational Linguistics; Natural Language Processing (NLP); Engineering; Digitale Signalverarbeitung (DSP); Computerlinguistik und Korpuslinguistik; Natürliche Sprachen und maschinelle Übersetzung; BC

Predicting Prosody from Text for Text-to-Speech Synthesis covers the specific aspects of prosody, mainly focusing on how to predict the prosodic information from linguistic text, and then how to exploit the predicted prosodic knowledge for various speech applications. Author K. Sreenivasa Rao discusses proposed methods along with state-of-the-art techniques for the acquisition and incorporation of prosodic knowledge for developing speech systems. Positional, contextual and phonological features are proposed for representing the linguistic and production constraints of the sound units present in the text. This book is intended for graduate students and researchers working in the area of speech processing.
Explores the intuitive relation between prosody and linguistic and production constraints Proposes non-linear models such as neural networks and support vector machines for capturing the prosodic information from the linguistic and production constraints Demonstrates the use of predicted prosodic knowledge for speech, speaker and language Includes supplementary material: sn.pub/extras