Modeling phone correlation for speaker adaptive speech recognition

Information of phone relationships is regarded as acting an important role in speech recognition. It has been successfully exploited in many speaker adaptation approaches. In this paper, we propose a new approach, named Phone Pair Model (PPM) re-scoring, to utilize phone relationships for speaker-adaptive speech recognition. PPM re-scoring approach does not really adapt model parameters to a new speaker. It just uses some pre-registered phones' samples from the speaker being recognized, to re-calculate the likelihood of phones that has been calculated on conventional phone HMMs, resulting in a more correct recognition result. Additionally, it can deal with not only inter-speaker acoustic variations but also intra-speaker acoustic variations adequately. Results of two recognition experiments, one using phone HMMs only and the other incorporating phone HMMs with the PPMs, showed that even by using only a few vowel samples as the pre-registered phones, PPM re-scoring approach brought an increase in recognition rate .