A New MFCC Improvement Method for Robust ASR

摘要：

The Mel-frequency cepstral coefficients (MFCC) are widely used for speech recognition.However,MFCC-based speech recognition performance degrades in presence of additive noise.In this paper,we propose a set of noise-robust features based on conventional MFCC feature extraction method.Our proposed method consists of two steps.In the first step,mel sub-band spectral subtraction is carried out.The second step consists of estimating SNR in each subband and defining a weight parameter based on this estimation.The weighting has been carried out in a way that gives more important roles in cepstrum parameter formation to sub-bands that are less affected by noise.Experimental results indicate that this method achieves improved performance for ASR in noisy environments.Furthermore,due to the simplicity of the implementation of our method,its computational overhead relative to MFCC is quite small.

作者: Hojatollah Yeganeh Seyed Mohammad Ahadi, Ali Ziaei

作者单位: Amirkabir University of Technology,Tehran,Iran

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）