| Paper: | SLP-L6.4 | ||
| Session: | Advances in LVCSR Algorithms | ||
| Time: | Wednesday, May 17, 17:30 - 17:50 | ||
| Presentation: | Lecture | ||
| Topic: | Speech and Spoken Language Processing: Decoding algorithms and implementation | ||
| Title: | TONE-ENHANCED GENERALIZED CHARACTER POSTERIOR PROBABILITY(GCPP) FOR CANTONESE LVCSR | ||
| Authors: | Yao Qian, Frank K. Soong, Microsoft Research Asia, China; Tan Lee, Chinese University of Hong Kong, China | ||
| Abstract: | Tone-enhanced, generalized character posterior probability (GCPP), a generalized form of posterior probability at subword (Chinese character) level, is proposed as a rescoring metric for improving Cantonese LVCSR performance. The search network is constructed first by converting the original word graph to a restructured word graph, then a character graph and finally, a character confusion network (CCN). Based upon GCPP enhanced with tone information, the character error rate (CER) is minimized or the GCPP product is maximized over a chosen graph. Experimental results show that the tone enhanced GCPP can improve character error rate by up to 15.1%, relatively. | ||
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