8th European Conference on Speech Communication and Technology

Geneva, Switzerland
September 1-4, 2003


Joint Model and Feature Based Compensation for Robust Speech Recognition Under Non-Stationary Noise Environments

Chuan Jia, Peng Ding, Bo Xu

Chinese Academy of Sciences, China

This paper presents a novel compensation approach, which is implemented in both model and feature spaces, for non-stationary noise Due to the nature of non-stationary noise which can be decomposed into constant part and residual noise part, our proposed scheme is performed in two steps: before recognition, an extended Jacobian adaptation (JA) is applied to adapt the speech models for the constant part of noise; during recognition, the power spectra of noisy speech are compensated to eliminate the effect of residual noise part of noise. As verified by the experiments performed under different stationary and non-stationary noise environments, the proposed JA is superior to the basic JA and the joint approach is better than the compensation in single space.

Full Paper

Bibliographic reference.  Jia, Chuan / Ding, Peng / Xu, Bo (2003): "Joint model and feature based compensation for robust speech recognition under non-stationary noise environments", In EUROSPEECH-2003, 985-988.