Using accent-specific pronunciation modelling for robust speech recognition

A method of modelling accent specific pronunciation variations is presented. Speech from an unseen accent group is phonetically transcribed such that pronunciation variations may be derived. These context dependent variations an clustered in a decision tree which is used as a model of the pronunciation variation associated with this new accent group. The tree is then used to build a new pronunciation dictionary for use during the recognition process. Experiments are presented for the recognition of Lancashire and Yorkshire accented speech using a recognizer trained on London and South East England speakers. The results show that the addition of accent specific pronunciations can reduce the error rate by almost 20% for cross accent recognition. It is also shown that worthwhile gains in performance can be obtained using only a small amount of accent specific data.