A comparison of approaches to automatic language identification using telephone speech

Abstract

A variety of approaches to language identification, based on (a) acoustic features, (b) broad-category segmentation, and (c) fine phonetic classification, are introduced. These approaches are evaluated in terms of their ability to distinguish between English and Japanese utterances spoken over a telephone channel. It is found that the best performance (86.3 % accurate classification of utterances with a mean length of 13.4 sec) is obtained when fine phonetic features are employed. In addition, the results show the importance of discriminatory training rather than likelihood estimation. 1. INTRODUCTION As developments in telecommunications and long-distance travel cause national borders to become increasingly transparent, the ability to identify which language is being spoken is growing in importance. The utility of tasks such as directory assistance or automatic translation is, for instance, improved substantially by the availability of a means of identifying which language is being s...