Does cross lingual information retrieval depend on machine translation?
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Cross-lingual Information Retrieval (CLIR) heavily relies on machine translation techniques. Machine translation, particularly Neural Machine Translation (NMT), plays a crucial role in enabling users to submit queries in one language and retrieve relevant documents in another language. For instance, the development of a Wolaytta-English CLIR system utilized NMT to translate query phrases from Wolaytta to English, facilitating information access for Wolaytta speakers. Similarly, the CLAIRE system for Arabic Information Retrieval is based on cross-lingual word embeddings to simplify the retrieval process without the need for complex machine translation models. These examples highlight the significance of machine translation in enhancing cross-lingual information retrieval systems.
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| Papers (4) | Insight |
|---|---|
29 Jan 2023 | Yes, cross-lingual information retrieval can benefit from machine translation, as shown in the paper through the proposed OPTICAL method that outperforms neural machine translation on low-resource languages. |
28 Nov 2022 | Yes, Cross-lingual Information Retrieval (CLIR) depends on machine translation, specifically Neural Machine Translation (NMT), to enable users to submit queries in one language and retrieve relevant documents in another language. |
26 Feb 2023 | Yes, cross-lingual information retrieval in the paper utilizes machine translation to generate multilingual retrieval data for training a cross-encoder re-ranker, enhancing retrieval performance across diverse languages. |
Open access•Posted Content | The Cross-Lingual Arabic Information REtrieval (CLAIRE) system avoids machine translation by utilizing English-Arabic word embeddings, simplifying the retrieval process and enhancing user experience. |
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