Papers with text machine translation

2 papers
A Simple Concatenation can Effectively Improve Speech Translation (2023.acl-short)

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Challenge: Experimental results show that in our unified cross-modal ST model, models can effectively utilize the auxiliary information from speech and text.
Approach: They propose a unified cross-modal ST method which concatenates speech and text as the input and builds a teacher that can utilize both cross-modities simultaneously.
Outcome: The proposed method can effectively utilize the auxiliary information from speech and text, and achieve compelling results on MuST-C datasets.
Exploring Better Text Image Translation with Multimodal Codebook (2023.acl-long)

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Challenge: Current studies on text image translation face bottlenecks due to lack of a publicly available dataset and poor optical character recognition.
Approach: They propose a text image translation model with a multimodal codebook and an OCR dataset for Chinese-English translation.
Outcome: The proposed model can associate the image with relevant texts, providing useful supplementary information for translation.

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