Fundamentals and Trends on Sound Source Separation : Overview of Approaches with Probabilistic Model and Deep Learning

DOI Web Site 109 References

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Other Title
  • 音源分離技術の基礎と動向
  • ―確率モデル/深層学習に基づく方法の概観―

Abstract

<p>Sound source separation, which separates multiple sound sources from a mixture, has continued to evolve by incorporating beamforming techniques in wireless communication, signal processing, optimization techniques based on probabilistic models, and deep learning techniques. This paper prondes an overview of sound source separation techniques for multiple microphones based on a spatial model and a probabilistic sound source model, for a single microphone with deep learning, and for multiple microphones using a deep-learning-based sound source model and a spatial model.</p>

Journal

  • IEICE ESS Fundamentals Review

    IEICE ESS Fundamentals Review 16 (4), 257-271, 2023-04-01

    The Institute of Electronics, Information and Communication Engineers

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