Using accent-specific pronunciation modelling for robust speech recognition

Abstract

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 are 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 & Yorkshire accented speech using a recognizer trained on London & 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.