CS2W: A Chinese Spoken-to-Written Style Conversion Dataset with Multiple Conversion Types (2023.emnlp-main)
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| Challenge: | Existing datasets focus on a single type of spoken style, such as disfluencies. |
| Approach: | They propose a Chinese Spoken-to-Written style conversion dataset with 7,237 spoken sentences extracted from transcribed conversational texts. |
| Outcome: | The proposed dataset covers four major conversion problems corresponding to the majority of spoken styles. |
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| Challenge: | Existing work on spoken-to-written transformations from older adults' language is limited by omission, disordered syntax, constituent errors, and redundancy. |
| Approach: | They propose to combine a spoken-to-written corpus of 10,004 utterances from older adults with a written version, fine-grained error labels, and four-sentence context. |
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WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem (2026.findings-acl)
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Chengyou Wang, Mingchen Shao, Jingbin Hu, Zeyu Zhu, Hongfei Xue, Bingshen Mu, Xin Xu, Xingyi Duan, Binbin Zhang, Zhu Pengcheng, Chuang Ding, Xiaojun Zhang, Hui Bu, Lei Xie
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Speech-to-Speech Translation for a Real-world Unwritten Language (2023.findings-acl)
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Peng-Jen Chen, Kevin Tran, Yilin Yang, Jingfei Du, Justine Kao, Yu-An Chung, Paden Tomasello, Paul-Ambroise Duquenne, Holger Schwenk, Hongyu Gong, Hirofumi Inaguma, Sravya Popuri, Changhan Wang, Juan Pino, Wei-Ning Hsu, Ann Lee
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| Challenge: | spoken-to-written style conversion is becoming an important technology to increase the readability of ASR transcriptions. |
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Writing System and Speaker Metadata for 2,800+ Language Varieties (2022.lrec-1)
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| Challenge: | Currently, language technologies are easily available in only a small minority of the world's 7,000+ language varieties. |
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CSSWiki: A Chinese Sentence Simplification Dataset with Linguistic and Content Operations (2024.lrec-main)
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| Challenge: | Current research focuses mainly on read operations and ignores other aspects of database operations such as create, update, and delete operations. |
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NaSGEC: a Multi-Domain Chinese Grammatical Error Correction Dataset from Native Speaker Texts (2023.findings-acl)
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| Challenge: | Recent studies on Chinese grammatical error correction focus on learning essays. |
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