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Evaluating Multilingual Speech Translation under Realistic Conditions with Resegmentation and Terminology

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We present the ACL 60/60 evaluation sets for multilingual translation of ACL 2022 technical presentations into 10 target languages.This dataset enables further research into multilingual speech translation under realistic recording conditions with unsegmented audio and domain-specific terminology, applying NLP tools to text and speech in the technical domain, and evaluating and improving model robustness to diverse speaker demographics.

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DOI
10.18653/v1/2023.iwslt-1.2
OpenAlex
W4385571086
Document type
conference-paper
Language
EN
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