关键词: 语音识别, 随机段模型, 声调建模, 发音特征, 阶层式多层感知器

Abstract: The tone model based on articulatory features is improved in this paper, and a framework is proposed which attempts to integrate the proposed tone model into stochastic segment based Mandarin speech recognition system. A set of seven articulatory features which represent the articulatory information is given. As well as prosodic features, the posteriors of speech signal belonging to the 35 pronunciation categories of articulatory features are used for tone modeling. The tone models are fused into the SSM-based speech recognition system after second pruning according to the property of segmental models. Tone recognition experiments conducted on “863-test” set indicate that about 3.11% absolute increase of accuracy can be achieved when using new articulatory features. When the proposed tone model is integrated into SSM system, the character error rate is reduced significantly. Thus, potential of the method is demonstrated.

Key words: speech recognition, stochastic segment modeling, tone modeling, articulatory feature, hierarchical multilayer perceptron classifiers