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Bandwidth Extension of Speech Using Perceptual Criteria / by Visar Berisha, Steven Sandoval, Julie Liss

By: Berisha, Visar, autor
Contributor(s): Sandoval, Steven, (1984-), autor | Liss, Julie Marie, autor
Material type: materialTypeLabelE-bookSeries: (Synthesis Lectures on Algorithms and Software in Engineering, 1938-1735).Publisher: Cham : Springer International Publishing, 2013Edition: 1st edition 2013.Description: 1 recurso en línea (XI, 71 páginas).ISBN: 9783031015212.Subject: Reconocimiento automático del lenguaje | Redes de banda ancha | AudiciónOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Acknowledgments -- Figure Credits -- Introduction -- Principles of Bandwidth Extension -- Psychoacoustics -- Bandwidth Extension Using Spline Fitting -- Summary -- Notation -- Bibliography -- Authors' Biographies.
Summary: Bandwidth extension of speech is used in the International Telecommunication Union G.729.1 standard in which the narrowband bitstream is combined with quantized high-band parameters. Although this system produces high-quality wideband speech, the additional bits used to represent the high band can be further reduced. In addition to the algorithm used in the G.729.1 standard, bandwidth extension methods based on spectrum prediction have also been proposed. Although these algorithms do not require additional bits, they perform poorly when the correlation between the low and the high band is weak. In this book, two wideband speech coding algorithms that rely on bandwidth extension are developed. The algorithms operate as wrappers around existing narrowband compression schemes. More specifically, in these algorithms, the low band is encoded using an existing toll-quality narrowband system, whereas the high band is generated using the proposed extension techniques. The first method relies only on transmitted high-band information to generate the wideband speech. The second algorithm uses a constrained minimum mean square error estimator that combines transmitted high-band envelope information with a predictive scheme driven by narrowband features. Both algorithms make use of novel perceptual models based on loudness that determine optimum quantization strategies for wideband recovery and synthesis. Objective and subjective evaluations reveal that the proposed system performs at a lower average bit rate while improving speech quality when compared to other similar algorithms.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TK7882.S65 2013 EB (Browse shelf(Opens below)) Acceso electrónico eBook.01112238
Total holds: 0

Acknowledgments -- Figure Credits -- Introduction -- Principles of Bandwidth Extension -- Psychoacoustics -- Bandwidth Extension Using Spline Fitting -- Summary -- Notation -- Bibliography -- Authors' Biographies.

Bandwidth extension of speech is used in the International Telecommunication Union G.729.1 standard in which the narrowband bitstream is combined with quantized high-band parameters. Although this system produces high-quality wideband speech, the additional bits used to represent the high band can be further reduced. In addition to the algorithm used in the G.729.1 standard, bandwidth extension methods based on spectrum prediction have also been proposed. Although these algorithms do not require additional bits, they perform poorly when the correlation between the low and the high band is weak. In this book, two wideband speech coding algorithms that rely on bandwidth extension are developed. The algorithms operate as wrappers around existing narrowband compression schemes. More specifically, in these algorithms, the low band is encoded using an existing toll-quality narrowband system, whereas the high band is generated using the proposed extension techniques. The first method relies only on transmitted high-band information to generate the wideband speech. The second algorithm uses a constrained minimum mean square error estimator that combines transmitted high-band envelope information with a predictive scheme driven by narrowband features. Both algorithms make use of novel perceptual models based on loudness that determine optimum quantization strategies for wideband recovery and synthesis. Objective and subjective evaluations reveal that the proposed system performs at a lower average bit rate while improving speech quality when compared to other similar algorithms.

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