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Quantum-Source Independent Component Analysis and Related Statistical Blind Qubit Uncoupling Methods Read chapter Read first chapter

2014 | OriginalPaper | Chapter

12. On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis

Authors : Christopher Hummersone, Toby Stokes, Tim Brookes

Published in: Blind Source Separation

Publisher: Springer Berlin Heidelberg

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Abstract

The ideal binary mask (IBM) is widely considered to be the benchmark for time–frequency-based sound source separation techniques such as computational auditory scene analysis (CASA). However, it is well known that binary masking introduces objectionable distortion, especially musical noise. This can make binary masking unsuitable for sound source separation applications where the output is auditioned. It has been suggested that soft masking reduces musical noise and leads to a higher quality output. A previously defined soft mask, the ideal ratio mask (IRM), is found to have similar properties to the IBM, may correspond more closely to auditory processes, and offers additional computational advantages. Consequently, the IRM is proposed as the goal of CASA. To further support this position, a number of studies are reviewed that show soft masks to provide superior performance to the IBM in applications such as automatic speech recognition and speech intelligibility. A brief empirical study provides additional evidence demonstrating the objective and perceptual superiority of the IRM over the IBM.

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previous chapter Speech Separation and Extraction by Combining Superdirective Beamforming and Blind Source Separation
next chapter Monaural Speech Enhancement Based on Multi-threshold Masking
Footnotes
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Metadata
Title
On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis
Authors
Christopher Hummersone
Toby Stokes
Tim Brookes
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
Book
Blind Source Separation

Print ISBN: 978-3-642-55015-7

Electronic ISBN: 978-3-642-55016-4

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-642-55016-4_12