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- W134600522 abstract "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." @default.
- W134600522 created "2016-06-24" @default.
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- W134600522 date "2008-09-22" @default.
- W134600522 modified "2023-10-18" @default.
- W134600522 title "Dialect recognition using adapted phonetic models" @default.
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- W134600522 doi "https://doi.org/10.21437/interspeech.2008-236" @default.
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