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

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Blind Source Separation

Part of the book series: Signals and Communication Technology ((SCT))

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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Notes

  1. 1.

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Acknowledgments

The authors would like to thank Nicoleta Roman and colleagues for providing the data for Table 12.4, Nilesh Madhu for providing the data for Table 12.6, and Jesper Jensen for providing the data for Table 12.7.

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  1. University of Surrey, Guildford, UK

    Christopher Hummersone, Toby Stokes & Tim Brookes

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  1. Christopher Hummersone
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Correspondence to Christopher Hummersone .

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  1. University of Technology, Sydney, Sydney, Australia

    Ganesh R. Naik

  2. University of Surrey, Guildford, United Kingdom

    Wenwu Wang

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Hummersone, C., Stokes, T., Brookes, T. (2014). On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis. In: Naik, G., Wang, W. (eds) Blind Source Separation. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55016-4_12

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

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