Vietnamese large vocabulary continuous speech recognition

Abstract

We report on our recent efforts toward a large vocabulary Vietnamese speech recognition system. In particular, we describe the Vietnamese text and speech database recently collected as part of our GlobalPhone corpus. The data was complemented by a large collection of text data crawled from various Vietnamese websites. To bootstrap the Vietnamese speech recognition system we used our Rapid Language Adaptation scheme applying a multilingual phone inventory. After initialization we investigated the peculiarities of the Vietnamese language and achieved significant improvements by implementing different tone modeling schemes, extended by pitch extraction, handling multiwords to address the monosyllable structure of Vietnamese, and featuring language modeling based on 5-grams. Furthermore, we addressed the issue of dialectal variations between South and North Vietnam by creating dialect dependent pronunciations and including dialect in the context decision tree of the recognizer. Our currently best recognition system achieves a word error rate of 11.7% on read newspaper speech.