论文信息 - Dialect recognition using adapted phonetic models

Dialect recognition using adapted phonetic models

In this paper, we introduce a dialect recognition method that makes use of phonetic models adapted per dialect without phonetically labeled data. We show that this method can be implemented efficiently within an existing PRLM[1] system. We compare the performance of this system with other state-of-theart dialect recognition methods (both acoustic and token-based) on the NIST LRE 2007 English and Mandarin dialect recognition tasks. Our experimental results indicate that this system can perform better than baseline GMM and adapted PRLM systems, and also results in consistent gains of 15-23% when combined with other systems.

Douglas A. Reynolds | Nancy F. Chen | Wade Shen

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