关键词: 维吾尔语, 声学模型, 语言模型, 维吾尔语音素, 基于隐马尔可夫模型的工具箱（HTK）

Abstract: In this paper, HTK （Hidden Markov model-based Toolkit） based Uyghur continuous phoneme recognition baseline system is presented, and its several language-depended key technologies are addressed. According to the characteristics of Uyghur language, it designs the text corpus for language modeling and speech corpus construction, and records a large-scale speech data for training the phoneme based Uyghur acoustic model. The different recognition rates with different N-gram language models are also given. The statistics of the recognition rates of 32 Uyghur phonemes, the list of the confused phonemes and their possible reasons are analyzed. And then it gives some research directions for further improvements to the baseline system.

Key words: Uyghur language, acoustic model, language model, Uyghur phoneme, Hidden Markov model-based Toolkit（HTK）