Recent Advances in Robust Speech Recognition Technology

by

Javier Ramírez, Juan Manuel Górriz

DOI: 10.2174/9781608051724111010
eISBN: 978-1-60805-172-4, 2011
ISBN: 978-1-60805-389-6



Indexed in: Scopus, EBSCO.

This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refe...[view complete introduction]
US $
Buy Personal Book
21
Order Library Book
84
Order Printed Copy
*119
Order PDF + Printed Copy (Special Offer)
*136

*(Excluding Mailing and Handling)

🔒Secure Checkout Personal information is secured with SSL technology

Statistical Model based Techniques for Robust Speech Communication

- Pp. 114-132 (19)

Nam Soo Kim and Joon-Hyuk Chang

Abstract

Acoustic interferences such as the background noise and reverberation are the major causes of quality degradation in speech communication. During the several decades, a huge number of attempts to reduce the effect of these interferences have been made by employing statistical model based techniques. In the statistical model based techniques, not only the clean speech source but also the background noise and acoustic echo are assumed to be generated from a class of parametric distributions for which there exist efficient methods to estimate the relevant parameters. In this chapter, we review the parametric models and their application to voice activity detection, noise reduction, and echo suppression, which are important preprocessing parts in robust speech communication systems.

Purchase Chapter  Book Details

Advertisement

Special New Year Discount

Webmaster Contact: info@benthamscience.net Copyright © 2019 Bentham Science