%0 Journal Article %A Ing-Jr Ding %D 2009 %J International Journal of Electrical and Computer Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 35, 2009 %T Improvement of MLLR Speaker Adaptation Using a Novel Method %U https://publications.waset.org/pdf/498 %V 35 %X This paper presents a technical speaker adaptation method called WMLLR, which is based on maximum likelihood linear regression (MLLR). In MLLR, a linear regression-based transform which adapted the HMM mean vectors was calculated to maximize the likelihood of adaptation data. In this paper, the prior knowledge of the initial model is adequately incorporated into the adaptation. A series of speaker adaptation experiments are carried out at a 30 famous city names database to investigate the efficiency of the proposed method. Experimental results show that the WMLLR method outperforms the conventional MLLR method, especially when only few utterances from a new speaker are available for adaptation. %P 2108 - 2113