Phonetics and Speech Sciences (말소리와 음성과학)

Korean Society of Speech Sciences (한국음성학회)
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Improvement of convergence speed in FDICA algorithm with weighted inner product constraint of unmixing matrix

분리행렬의 가중 내적 제한조건을 이용한 FDICA 알고리즘의 수렴속도 향상

  • Received : 2015.11.12
  • Accepted : 2015.12.14
  • Published : 2015.12.31
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Abstract

For blind source separation of convolutive mixtures, FDICA(Frequency Domain Independent Component Analysis) algorithms are generally used. Since FDICA algorithm such as Sawada FDICA, IVA(Independent Vector Analysis) works on the frequency bin basis with a natural gradient descent method, it takes much time to converge. In this paper, we propose a new method to improve convergence speed in FDICA algorithm. The proposed method reduces the number of iteration drastically in the process of natural gradient descent method by applying a weighted inner product constraint of unmixing matrix. Experimental results have shown that the proposed method achieved large improvement of convergence speed without degrading the separation performance of the baseline algorithms.

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References

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