A Segment-Based Automatic Language Identification System

We have developed a four-language automatic language identification system for high-quality speech. The system uses a neural network-based segmentation algorithm to segment speech into seven broad phonetic categories. Phonetic and prosodic features computed on these categories are then input to a second network that performs the language classification. The system was trained and tested on separate sets of speakers of American English, Japanese, Mandarin Chinese and Tamil. It currently performs with an accuracy of 89.5% on the utterances of the test set.