A Hybrid Nonlinear ANC for Speech Recovery Using Both Bone- and Air-Conducted Measurements
Ran Xiao*1, Yaping Ma*2, Boyan Huang*2, Yegui Xiao*3, and Koji Hasegawa*4
*1NEC Solution Innovators, Ltd.
1-40-1 Tomominami, Asaminami-ku, Hiroshima 731-3168, Japan
*2Harbin Institute of Technology
Box 351, Harbin 150001, China
*3Prefectural University of Hiroshima
1-1-71 Ujina-Higashi, Minami-ku, Hiroshima 734-8558, Japan
*4Hiroshima Prefectural Technology Research Institute
10-52 Motomachi, Naka-ku, Hiroshima 730-8511, Japan
Speech recovery in the presence of very harsh noise is calling for R&D that take approaches different from those established to date, as the conventional systems and algorithms for speech denoising may suffer from serious performance degradation. In this paper, we propose a hybrid nonlinear adaptive noise canceller (ANC) to perform the speech enhancement task using both bone- and air-conducted measurements. In the proposed ANC, the bone-conducted speech serves as a reference signal while the air-conducted measurement with very large additive noise is adopted as a primary noise. A Volterra filter and a functional link artificial neural network (FLANN) are placed in parallel, forming a hybrid nonlinear ANC. Simulations using real bone- and air-conducted speech measurements are provided to demonstrate that the proposed system outperforms ANCs equipped with FIR filter or Volterra filter or FLANN alone.
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