Papers by Kosuke Doi

2 papers
NAIST-SIC-Aligned: An Aligned English-Japanese Simultaneous Interpretation Corpus (2024.lrec-main)

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Challenge: Simultaneous interpretation data is a task where an utterance is translated in real-time.
Approach: They propose to use an automatically-aligned parallel English-Japanese SI dataset to make it suitable for model training.
Outcome: The proposed model improves translation quality and latency over baselines.
Simul-COMET: A Quality Metric for Simultaneous Interpretation in Distant Language Pair Considering Word Order Difference (2026.findings-acl)

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Challenge: Simultaneous interpretation (SI) uses segmenting of source speech into chunks and translating them in order.
Approach: They propose a variation of COMET that measures monotonicity for simultaneous interpretation . they train Simul-COMET on offline translation data and show stronger alignment with evaluation scores .
Outcome: The proposed model shows stronger alignment with evaluation scores provided by interpreters than COMET.

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