Papers with English to French
French Biomedical Text Simplification: When Small and Precise Helps (2020.coling-main)
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| Challenge: | Existing studies on text simplification in English use large parallel monolingual corpora in which one complex sentence is paired with one or more simplified versions. |
| Approach: | They use parallel sentences from existing health comparable corpora in French and WikiLarge corpus translated from English to French and a lexicon that associates medical terms with paraphrases. |
| Outcome: | The proposed models are based on sentences from existing health comparable corpora in French and WikiLarge corpus translated from English to French. |
Evaluating Discourse Phenomena in Neural Machine Translation (N18-1)
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| Challenge: | Existing models for machine translation have been evaluated with standard automatic metrics, but are poorly adapted to evaluating discourse phenomena. |
| Approach: | They propose to use BLEU to train multi-encoder NMT models on English subtitles to test their ability to exploit previous source and target sentences. |
| Outcome: | The proposed multi-encoder models give limited improvements on the coreference and coherence tests. |
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation (2023.findings-emnlp)
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| Challenge: | Modern artificial intelligence is characterized by large pretrained language models with strong language capabilities to be adapted to various downstream tasks. |
| Approach: | They propose to use the task of speech translation (ST) to pretrain speech models for end-to-end SLU on intra- and cross-lingual scenarios. |
| Outcome: | The proposed model achieves higher performance over baselines on monolingual and multilingual intent classification as well as spoken question answering using SLURP, MINDS-14, and NMSQA benchmarks. |
Multimodal Lexical Translation (L18-1)
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| Challenge: | Multimodal Lexical Translation (MLT) is a task that aims to translate ambiguous words given their context -an image and a sentence in the source language. |
| Approach: | They introduce a task to translate an ambiguous word given its context -an image and a sentence in the source language. |
| Outcome: | The proposed task is based on the Multi30K dataset and uses word-alignment followed by human inspection to select subsets of the dataset which are difficult to translate. |
New Datasets for Automatic Detection of Textual Entailment and of Contradictions between Sentences in French (2024.lrec-main)
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| Challenge: | DACCORD is a dataset for automatic detection of contradictions between sentences . it is the first dataset exclusively dedicated to this task . |
| Approach: | They introduce DACCORD, a dataset in French for automatic detection of contradictions between sentences. |
| Outcome: | The proposed datasets are more challenging than existing datasets for the mainstream task in French. |