From Simultaneous to Streaming Machine Translation by Leveraging Streaming History
Javier Iranzo-Sánchez, Jorge Civera, Alfons Juan-Císcar
Abstract
Simultaneous Machine Translation is the task of incrementally translating an input sentence before it is fully available. Currently, simultaneous translation is carried out by translating each sentence independently of the previously translated text. More generally, Streaming MT can be understood as an extension of Simultaneous MT to the incremental translation of a continuous input text stream. In this work, a state-of-the-art simultaneous sentencelevel MT system is extended to the streaming setup by leveraging the streaming history. Extensive empirical results are reported on IWSLT Translation Tasks, showing that leveraging the streaming history leads to significant quality gains. In particular, the proposed system proves to compare favorably to the best performing systems.
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Cited by top-tier papers2
- Self-Modifying State Modeling for Simultaneous Machine TranslationDonglei Yu, Xiaomian Kang, Yuchen Liu, Yu Zhou et al.ACL 2024
- StreamAtt: Direct Streaming Speech-to-Text Translation with Attention-based Audio History SelectionSara Papi, Marco Gaido, Matteo Negri, Luisa BentivogliACL 2024
Builds on2
- Direct Segmentation Models for Streaming Speech TranslationJavier Iranzo-Sánchez, Adrià Giménez-Pastor, Joan Albert Silvestre-Cerdà, Pau Baquero-Arnal et al.EMNLP 2020 · 24 citations
- Beyond Sentence-Level End-to-End Speech Translation: Context HelpsBiao Zhang, Ivan Titov, Barry Haddow, Rico SennrichACL 2021
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