Chat Translation Error Detection for Assisting Cross-lingual Communications
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Abstract (arXiv)
In this paper, we describe the development of a communication support system that detects erroneous translations to facilitate crosslingual communications due to the limitations of current machine chat translation methods. We trained an error detector as the baseline of the system and constructed a new Japanese-English bilingual chat corpus, BPersona-chat, which comprises multiturn colloquial chats augmented with crowdsourced quality ratings. The error detector can serve as an encouraging foundation for more advanced erroneous translation detection systems.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 15 of its 28 references that are in the map. First posted on arXiv 2 Aug 2023.
Builds on
15 of 28 references.
References · 15
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
- 2015Neural Machine Translation of Rare Words with Subword Unitscited by 2,898
- 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,486
- 2016Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translationcited by 1,471
- 2018Personalizing Dialogue Agents: I have a dog, do you have pets too?cited by 820
- 2018Scaling Neural Machine Translationcited by 204
- 2017Neural Machine Translation with Extended Contextcited by 95
- 2018Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluationcited by 88
- 2018Attaining the Unattainable? Reassessing Claims of Human Parity in Neural Machine Translationcited by 58
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3 papers.