Papers with multi-modal machine translation
Whisper-UT: A Unified Translation Framework for Speech and Text (2025.emnlp-main)
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Cihan Xiao, Matthew Wiesner, Debashish Chakraborty, Reno Kriz, Keith Cunningham, Kenton Murray, Kevin Duh, Luis Tavarez-Arce, Paul McNamee, Sanjeev Khudanpur
| Challenge: | Encoder-decoder models have achieved remarkable success in speech and text tasks, but efficiently adapting them to diverse uni/multimodal scenarios remains a challenge. |
| Approach: | They propose a framework that leverages lightweight adapters to enable seamless adaptation across tasks. |
| Outcome: | The proposed framework improves speech translation performance through a 2-stage decoding strategy without requiring 3-way parallel data. |
Probing Multi-modal Machine Translation with Pre-trained Language Model (2021.findings-acl)
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| Challenge: | Multi-modal machine translation (MMT) aimed at using images to help disambiguate the target during translation but recent studies showed that visual features are either negligible or incremental. |
| Approach: | They propose to incorporate a visual language model on the source side to improve multi-modal translation quality significantly. |
| Outcome: | The proposed model improves the translation quality significantly on the multi-modal dataset. |