Using multilingual units for improved modeling of pronunciation variants

Standard speech modeling generally implies the combination of models of the phonemes of the current language with a description of possible pronunciation variants of the vocabulary words. When dealing with foreign accent, this standard native speech modeling is not adequate. In fact many variabilities have to be taken into account as the acoustic realization of the sounds by non-native speakers does not always match with native models and some phonemes may be replaced by others. By introducing models of phonemes estimated from speech data of other languages, and adding extra pronunciation variants through phonological rules, speech recognition performance improvements were achieved on non-native speech. In this study, a selection of the most frequently used variants is proposed, which relies on the frequency of usage of the various models associated to each phoneme on a development set. Although this selection process is rather simple it provides significant performance improvement.