Papers with Cross-lingual Information Retrieval
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages (2020.coling-main)
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Diptesh Kanojia, Raj Dabre, Shubham Dewangan, Pushpak Bhattacharyya, Gholamreza Haffari, Malhar Kulkarni
| Challenge: | a study of 14 Indian languages shows that cognates can be detected by word embeddings . cognates are variants of the same lexical form across languages . |
| Approach: | They propose to use cross-lingual word embeddings to detect cognates among 14 Indian languages . they then evaluate the impact of their method on neural machine translation . |
| Outcome: | The proposed method improves on a dataset of 12 Indian languages . it also improves quality of the extracted cognates by up to 2.76 BLEU . |
A Multi-Task Architecture on Relevance-based Neural Query Translation (P19-1)
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| Challenge: | Existing models for cross-lingual information retrieval are not aware of the vocabulary distribution of the retrieval corpus. |
| Approach: | They propose a multi-task learning approach to train a Neural Machine Translation model with a Relevance-based Auxiliary Task (RAT) for search query translation. |
| Outcome: | The proposed model achieves 16% improvement over a strong baseline on Italian-English query-document dataset. |