Recent Advances in Robust Speech Recognition Technology

Speech Enhancement Algorithms: A Survey

Author(s): Philipos C. Loizou

Pp: 60-102 (43)

DOI: 10.2174/978160805172411101010060

* (Excluding Mailing and Handling)

Abstract

The need to remove or suppress acoustic noise arises in many situations in which the voice signal originates from a noisy location or is affected by noise over a communication channel. This Chapter presents an up-to-date coverage of all major noise suppression algorithms proposed over the past two decades including spectral subtractive algorithms, Wiener filtering, statistical-model based algorithms and subspace algorithms. It presents a comprehensive evaluation and comparison of major enhancement algorithms in terms of speech quality and speech intelligibility. Finally, this hapter concludes with a description of major objective measures used for predicting the subjective quality and intelligibility of noise-suppressed speech.


Keywords: Spectral subtractive algorithms, statistical-based speech enhancement, modulation filtering, subspace methods.

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