Pattern-Based Dynamic Compensation to Improve the Robustness of Speech Recognition in Mobile Environments
Wang Ya-xun · Modern Computer · 2008
Proposes a Pattern-based Dynamic Compensation(PDC) scheme to improve the robustness of ASR in mobile environments. In PDC, a distortion pattern-set is employed to normalize the environmental variations in training data according to a set of pre-defined application scenarios. At recognition time, instantaneous distortion is calculated as a linear combination of several possible patterns. To online estimate the combination weights robustly, a Bayesian learning process with Speech-conditioned Prior Evolution is introduced into PDC(PDC-SPE).In outdoor experiments, the PDC-SPE method outperforms other commonly used compensation/adaptation methods and leads to 20~25% relative reduction in Word Error Rate(WER) over a well-trained baseline system.