Design of echo cancellation and noise elimination for speech enhancement

In this paper, we present the new methods to cancel echo especially for the short path (e.g. car) and eliminate noise for speech enhancement. An adaptive filter based on the delayed error least mean square algorithm is used to cancel echo. The external noise is eliminated and the clean speech is estimated by using the Kalman filter and the spectral subtraction technique. To be suitable for use in consumer electronics, we also design a high speed and flexible VLSI architecture of the adaptive filter for canceling echo. The architecture has hardware utilization efficiency of 100%, and we can easily scale the filter without reducing the throughput rate. The 0.6 /spl mu/m CMOS SPTM standard cells technology has been used to implement the chip. The experimental results demonstrate the effectiveness of the proposed methods.

[1]  Fuyun Ling,et al.  Corrections to 'The LMS algorithm with delayed coefficient adaptation' , 1992, IEEE Trans. Signal Process..

[2]  Raziel Haimi-Cohen,et al.  A systolic array realization of an LMS adaptive filter and the effects of delayed adaptation , 1992, IEEE Trans. Signal Process..

[3]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[4]  R. Tucker,et al.  Voice activity detection using a periodicity measure , 1992 .

[5]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[6]  Kah-Chye Tan,et al.  Postprocessing method for suppressing musical noise generated by spectral subtraction , 1998, IEEE Trans. Speech Audio Process..

[7]  T. Meng,et al.  Arbitrarily high sampling rate adaptive filters , 1987, IEEE Trans. Acoust. Speech Signal Process..

[8]  S. Boll,et al.  Suppression of acoustic noise in speech using spectral subtraction , 1979 .

[9]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[10]  Fuyun Ling,et al.  The LMS algorithm with delayed coefficient adaptation , 1989, IEEE Trans. Acoust. Speech Signal Process..

[11]  Ramdas Kumaresan,et al.  On designing stable allpass filters using AR modeling , 1999, IEEE Trans. Signal Process..

[12]  J. Thomas.  A delayed error least mean squares adaptive filtering algorithm and its performance analysis , 1996, 1996 IEEE Digital Signal Processing Workshop Proceedings.

[13]  Joseph Thomas,et al.  Pipelined systolic architectures for DLMS adaptive filtering , 1996, J. VLSI Signal Process..