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Real-time blind audio source separation: performance assessment on an advanced digital signal processor

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Abstract

Many on-line blind audio source separation (BASS) algorithms have been presented so far to the scientific community, but only a few of them have been evaluated in terms of their real-time performance. In this paper we consider a well-established BASS method (oriented to voices separation) evaluating its performance in terms of separation quality allowed by a real-time embedded computing implementation, also considering novel and state-of-the-art improvements to the it. To this aim, the algorithm has been implemented and ported for real-time execution onto an advanced low-power digital signal processor targeted for complex-domain applications. The optimized embedded implementation is able to perform up to five iterations of the gradient for any input frame of data, achieving good separation levels (up to 11.8 dB of signal to interference ratio on custom recording in real environments). The proposed solution doubles the performance of a C-optimized version running on a traditional PC processor, achieving a better separation result with lower power requirements.

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Acknowledgments

The authors wish to thank Dr. Gianmarco Angius for his help with the realization of the recording setup and the sound engineers Matteo Bucca and Carla Pisano for their kind help and the useful suggestions.

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  1. Alessandro Pani

    Present address: Telit Communications S.p.A, Cagliari, Italy

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, University of Cagliari, Via Marengo, 3, 09123 , Cagliari, Italy

    Danilo Pani, Alessandro Pani & Luigi Raffo

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  1. Danilo Pani
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  2. Alessandro Pani
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  3. Luigi Raffo
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Correspondence to Danilo Pani.

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Pani, D., Pani, A. & Raffo, L. Real-time blind audio source separation: performance assessment on an advanced digital signal processor. J Supercomput 70, 1555–1576 (2014). https://doi.org/10.1007/s11227-014-1252-4

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