mlsanityData to 7 Oct 2026

JESC: Japanese-English Subtitle Corpus

arXiv 1710.10639 ↗First posted 29 Oct 2017cs.CLcited by 16

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Abstract (arXiv)

In this paper we describe the Japanese-English Subtitle Corpus (JESC). JESC is a large Japanese-English parallel corpus covering the underrepresented domain of conversational dialogue. It consists of more than 3.2 million examples, making it the largest freely available dataset of its kind. The corpus was assembled by crawling and aligning subtitles found on the web. The assembly process incorporates a number of novel preprocessing elements to ensure high monolingual fluency and accurate bilingual alignments. We summarize its contents and evaluate its quality using human experts and baseline machine translation (MT) systems.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Oct 2017.

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Citing papers per year: 2021: 4; 2022: 3; 2023: 3; 2024: 3; 2025: 3.

16 papers.

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  1. 2023MADLAD-400: A Multilingual And Document-Level Large Audited Datasetcited by 180
  2. 2021MURAL: Multimodal, Multitask Retrieval Across Languagescited by 44
  3. 2022JParaCrawl v3.0: A Large-scale English-Japanese Parallel Corpuscited by 17
  4. 2022Controlling Translation Formality Using Pre-trained Multilingual Language Modelscited by 14
  5. 2022SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakescited by 9
  6. 2024Enhancing Translation Accuracy of Large Language Models through Continual Pre-Training on Parallel Datacited by 7
  7. 2023llm-japanese-dataset v0: Construction of Japanese Chat Dataset for Large Language Models and its Methodologycited by 6
  8. 2024KazParC: Kazakh Parallel Corpus for Machine Translationcited by 5
  9. 2021Monotonic Simultaneous Translation with Chunk-wise Reordering and Refinementcited by 4
  10. 2025MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMscited by 4
  11. 2023Ask Language Model to Clean Your Noisy Translation Datacited by 3
  12. 2024Simultaneous Interpretation Corpus Construction by Large Language Models in Distant Language Paircited by 3
4 more
  1. 2025Misspellings in Natural Language Processing: A surveycited by 3
  2. 2025MockConf: A Student Interpretation Dataset: Analysis, Word- and Span-level Alignment and Baselinescited by 1
  3. 2021Repairing Pronouns in Translation with BERT-Based Post-Editingcited by 0
  4. 2021Learning Neural Models for Natural Language Processing in the Face of Distributional Shiftcited by 0