| Download | - View final version: Continual learning for Parliamentary Neural Machine Translation systems (PDF, 45.1 MiB)
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| DOI | Resolve DOI: https://doi.org/10.4224/40003539 |
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| Author | Search for: Knowles, Rebecca1ORCID identifier: https://orcid.org/0000-0002-1647-584X; Search for: Larkin, Samuel1ORCID identifier: https://orcid.org/0009-0000-6147-9631; Search for: Simard, Michel1ORCID identifier: https://orcid.org/0009-0002-5317-3063; Search for: Tessier, Marc1ORCID identifier: https://orcid.org/0009-0009-1413-2892; Search for: Bernier-Colbourne, Gabriel1; Search for: Goutte, Cyril1ORCID identifier: https://orcid.org/0000-0003-4939-6555; Search for: Lo, Chi-kiu1ORCID identifier: https://orcid.org/0000-0001-8714-7846 |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Technical Report |
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| Physical description | 28 p. |
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| Abstract | This report describes experiments on continual learning for Parliamentary Neural Machine Translation systems used to automatically translate between English (EN) and French (FR). The goal is to provide a proofof- concept of a simple approach to continual learning—a process in which new translations are used to regularly iteratively update a translation model, better incorporating new terminology and changes in preferred translations—in the setting of machine translation for the House of Commons of Canada. |
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| Publication date | 2025 |
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| Publisher | National Research Council of Canada |
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| Related publication | |
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| Language | English |
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| Peer reviewed | No |
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| NRC number | NRC-DT-903 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 24fdc03f-f683-4251-b333-d6f85bf4d606 |
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| Record created | 2025-07-25 |
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| Record modified | 2025-07-28 |
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