Papers with DEEP
DEEP: an automatic bidirectional translator leveraging an ASR for translation of Italian sign language (2025.acl-demo)
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Nicolas Tagliabue, Elisa Colletti, Francesco Roberto Dani, Roberto Tedesco, Sonia Cenceschi, Alessandro Trivilini
| Challenge: | DEEP is a bidirectional translation system for the Italian Sign Language . it is designed for pharmacies and the registry office of the municipality . |
| Approach: | They propose a bidirectional translation system for the Italian Sign Language, DEEP . the system allows deaf people to interact with a virtual LIS interpreter and a chat UI . |
| Outcome: | The proposed system can be used in pharmacies and the registry office of the municipality. |
DEEP: DEnoising Entity Pre-training for Neural Machine Translation (2022.acl-long)
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| Challenge: | Earlier named entity translation methods focus on phonetic transliteration, which ignores the sentence context for translation. |
| Approach: | They propose a DEnoising Entity Pre-training method that leverages monolingual data and a knowledge base to improve named entity translation accuracy within sentences. |
| Outcome: | The proposed method improves on three language pairs and denoising auto-encoding baselines. |