Modeling Uyghur Speech Phenomena with Morphological Rules

Title:Modeling Uyghur Speech Phenomena with Morphological Rules

Volume: 8 Issue: 1

Author(s): Huajian Xue, Ronghui Zhang, Haiwei Wang, Wenxiao Zeng and Chongke Bi

Affiliation:

Keywords: Morpheme, machine learning, pronunciation variation, uyghur, voice search application.

Abstract: Due to the morphology of Uyghur, it poses a challenge to state-of-the-art speech recognition systems. This paper describes our work on Uyghur speech recognition technology and a Uyghur voice search application with recent patents on them. Firstly, we introduce the morphology of Uyghur and Uyghur speech phenomena. Secondly, we investigate the use of morphemes in Uyghur auto speech recognition. When speech phenomena happen, variant surface forms of the morpheme are produced. Then, we describe a new approach utilizing the morphological rules to model speech phenomena. In this new approach, variant surface forms are replaced by their corresponding original stems. This creates a better pronunciation lexicon and a more robust language model in Uyghur speech recognition experiments. Finally, we apply the new morphemebased speech recognition approach to a Uyghur voice search application. Experimental results show that this new approach gives the best results in both speech recognition experiments and voice search experiments.

Cite this article as:

Xue Huajian, Zhang Ronghui, Wang Haiwei, Zeng Wenxiao and Bi Chongke, Modeling Uyghur Speech Phenomena with Morphological Rules, Recent Patents on Computer Science 2015; 8 (1) . https://dx.doi.org/10.2174/2213275907666141027213855