English-Chinese bilingual text-independent speaker verification

This paper describes the development of a text-independent speaker verification (TISV) system for English and Chinese utterances. We have designed and collected a bilingual database that contains spoken responses and commands in short, medium and long durations. The TISV system uses Gaussian mixtures for speaker models. Our experiments indicate that language mismatch between enrolment and verification data leads to significant degradation in verification performance (between 40% to 49%). In order to maximize robustness towards language change in test utterances, speaker models were trained with utterances from both languages. Results indicate that this can effectively close the performance degradation gap due to language mismatch as mentioned above.