Building Large-Scale Japanese Pronunciation-Annotated Corpora for Reading Heteronymous Logograms (2022.lrec-1)
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| Challenge: | Especially in Japanese, there are many common heteronyms expressed by logograms (Chinese characters or kanji) that have totally different pronunciations. |
| Approach: | They construct large-scale Japanese corpora that annotate kanji characters with their pronunciations to improve the accuracy of pronunciation prediction models. |
| Outcome: | The proposed models achieve an average accuracy of 0.939 for 203 common heteronyms and a 0.938 for 93 heters. |
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