This paper describes the challenges in Uyghur speech recognition caused by rich morphology of this language and a new morpheme-based approach to overcome them. Standard morpheme-based approach is also investigated in this paper and outperforms word-based approach. However, this approach pays no attention to frequent vowel weakening of Uyghur that potentially increases the number of morphemes and reduces the effect of the morpheme-based approach. In the new approach, vowel weakening surface forms are replaced by their corresponding stems in lexicon building and language modeling in order to make more effective vocabulary and more robust language model. Then, The vocabulary and language model are utilized in the experiments. Experimental results show that this new approach gives the best result and performs better than standard morpheme-based approach.