Abstract
This study addresses the problem of channel effect in the line spectrum frequency (LSF) domain. LSF parameters are the popular speech features encoded in the bit stream for low bit-rate speech transmission. A method of channel effect compensation in LSF domain is of interest for robust speech recognition on mobile communication and Internet systems. If the bit error rate in the transmission of digital encoded speech is negligibly low, the channel distortion comes mainly from the microphone or the handset. When the speech signal is represented in terms of the phase of inverse filter derived from LP analysis, this channel distortion can be expressed in terms of the channel phase. Further derivation shows that the mean subtraction performed on the phase of inverse filter can minimize the channel effect. Based on this finding, an iterative algorithm is proposed to remove the bias on LSFs due to channel effect. The experiments on the simulated channel distorted speech and the real telephone speech are conducted to show the effectiveness of our proposed method. The performance of the proposed method is comparable to that of cepstral mean normalization (CMN) in using cepstral coefficients.
Highlights
Channel distortion is always a serious problem in speech recognition systems
The line spectrum frequency (LSF) parameters show the poor performance in a large vocabulary continuous speech recognition (LVCSR) system, they can obtain comparable performance as cepstral coefficients do in connected digits recognition or small vocabulary speech recognition systems [12, 13]
When the speech signal is represented by the phase of inverse filter, the channel distortion can be expressed in terms of the channel phase [21]
Summary
Channel distortion is always a serious problem in speech recognition systems. Channel distortion may drastically degrade the performance of speech recognition [1, 2, 3]. Many approaches have been proposed for eliminating the influence of channel distortion to speech recognition performance [4, 5, 6, 7, 8, 9]. Further derivation shows that the mean subtraction performed on the phase of inverse filter can minimize the channel effect. Based on this finding, an iterative algorithm is proposed to remove the bias on LSFs due to channel effect. The first series of experiments use simulated channel distorted speech to examine the channel effect on a digital communication system due to the handset distortion and the effect of codec process.
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