该文对不同语速下,人工标注的维吾尔语连续语音语料中各音素进行共振峰频率、音长、音强的统计分析,并完成辅-元结构下的塞音、塞擦音的声学特征分析。该文通过美尔频率倒谱系数与共振峰频率等声学特征的融合及模型状态数的修改,对维吾尔语音素识别的声学模型进行了改进,并验证了不同声学特征对音素识别的影响。相比于基线系统,改进后声学模型的识别率取得一定提升。同时,利用语音学知识分析维吾尔语易混淆音素产生原因,为音素识别声学模型的进一步改进提供参考依据。

Employing manually labeled continuous speech sentences, this paper conducts an analysis of each Uyghur phonemes formant frequency, duration and intensity by the classification of speech rate. To study Uyghur plosive and affricate, the paper makes the analysis of their acoustic feature under the structure of consonant-vowel. Feature fusion and the change of models state number are applied to validate the influences of different acoustic features to the Uyghur phoneme recognition. It also describes an improved acoustic model with a higher recognition rate. Meanwhile, the analysis of confusing phonemes provides a reference for the further improvement of Uyghur acoustic models.