ADAPTIVE MODEL COMBINA SPEAKER SELECTIO

Acoustic variability across speakers is one of the challenges of speaker independent speech recognition systems. In this paper we propose a two-stage speaker selection training method for speaker adaptation. After cohort speakers are selected for test speaker, an adaptive model combination method is developed to replace the formerly used retraining process. In addition, impacts of number of selected cohort speakers and number of utterances from test speaker are investigated. Preliminary experiments on dynamic speaker selection are shown. Relative error rate reduction of 12.27% is achieved when only 10 utterances are available. Finally, further extensions of model combination scheme and dynamic selection are discussed. 1