语音识别中最小音素错误特征训练的研究

ue to the limitation of the traditional maximum likelihood training criteria, the research about the discriminative training has become a hot topic in the field of speech recognition. It is applied to practical and has improved the recognition performance. The research is expanded from various aspects. This paper is focus on the feature-MPE. It uses the minimum phone error training criteria to guide the feature transformation, parameter update and model training. The research aims to adjust the feature vector to optimize the objective function. The research includes a high-dimensional feature vectors and transformation matrix. The experiments show the algorithm can improve the correct word rate.(MLE:3.8%. MPE:1.2%)