Robust Speech Recognition Using a Harmonic
Model
许超;曹志刚
【期刊名称】《清华大学学报（英文版）》 【年(卷),期】2004(009)002
【摘要】Automatic speech recognition under conditions of a noisy environment remains a challenging problem. Traditionally, methods focused on noise structure, such as spectral subtraction, have been employed to address this problem, and thus the performance of such methods depends on the accuracy in noise estimation. In this paper, an alternative method, using a harmonic-based spectral reconstruction algorithm, is proposed for the enhancement of robust automatic speech recognition. Neither noise estimation nor noise-model training are required in the proposed approach. A spectral subtraction integrated autocorrelation function is proposed to determine the pitch for the harmonic model. Recognition results show that the harmonic-based spectral reconstruction approach outperforms spectral subtraction in the middle- and low-signal noise ratio (SNR) ranges. The advantage of the proposed method is more manifest for non-stationary noise, as the algorithm does not require an assumption of stationary noise. 【总页数】5页(202-206)
【关键词】robust speech recognition;speech enhancement;pitch
Robust Speech Recognition Using a Harmonic Model
