Papers with Europarl
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation (L18-1)
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| Challenge: | Recent work in spoken language translation (SLT) has attempted to build end-to-end speech-totext translation without using source language transcription during learning or decoding. |
| Approach: | They propose to augment an existing (monolingual) corpus: LibriSpeech. |
| Outcome: | The proposed corpus is derived from read audiobooks from the LibriVox project and has been carefully segmented and aligned. |
Revamping Multilingual Agreement Bidirectionally via Switched Back-translation for Multilingual Neural Machine Translation (2024.findings-eacl)
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| Challenge: | Current multilingual agreement (MA) methods require parallel data between multiple language pairs, which is not always realistic and optimize the agreement in an ambiguous direction, which hampers the translation performance. |
| Approach: | They propose a novel multilingual agreement framework that optimizes agreement bidirectionally with the Kullback-Leibler Divergence loss. |
| Outcome: | The proposed method improves strong baselines on the task of multilingual neural machine translation with three benchmarks: TED Talks, News, and Europarl. |
Unsupervised Statistical Machine Translation (D18-1)
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| Challenge: | Neural Machine Translation (NMT) systems can be trained from monolingual corpora without supervision. |
| Approach: | They propose a phrase-based approach that trains from monolingual corpora . their method is based on phrase-driven Statistical Machine Translation (SMT) they propose to train NMT systems without supervision from monolinguistic corpors . |
| Outcome: | The proposed approach improves on the existing supervised systems by combining a phrase table with an n-gram language model and fine-tuning hyperparameters through an unsupervised MERT variant. |
Better OOV Translation with Bilingual Terminology Mining (P19-1)
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| Challenge: | Unseen words, also called out-of-vocabulary words, are difficult for machine translation . byte-pair encoding can be used to represent OOVs, but they are often incorrectly translated . |
| Approach: | They propose to use monolingual data to improve the translation of unseen words . they use five target language words to mine target-language sentences . |
| Outcome: | The proposed system can be used to improve translation of out-of-vocabulary words (OOVs) the proposed system is trained on Europarl and can be fine-tuned to improve the translation quality. |