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Lepage Lab
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A natural language processing lab that advances translation by using similarities in the form of language as clues.
AboutAbout the lab
Learning from examples to connect languages.
The Lepage Lab studies example-based machine translation and natural language processing.
With the spread of the web, text written in the world's languages has grown rapidly, and the need to obtain information in other languages is increasing.
The example-based approach in natural language processing aims to combine a low cost of application with the ability to generate language productively.
The lab is clarifying the form of this example-based approach and applying it to tasks such as automatic generation of multilingual dictionaries, paraphrasing, and automatic translation.
Key terms
- Natural language processing
- The field of technology for making computers handle the language people use in everyday life
- Analogical relation
- A correspondence among four elements of the form "the relation between A and B is the same as the relation between C and D"
- Low-resource language
- A language with little available text or data, so there is not enough material to train machine translation
NewsLab news
View More ↗ResearchResearch themes
The Lepage Lab engages in cutting-edge research in natural language processing, with particular emphasis on analogy and analogical relations, learning from examples, and machine translation. It combines theoretical inquiry with experiments, aiming to produce new insights and methods.
*Illustrative imageResearch on analogical relations
The lab investigates ways to make the computation of analogical relations more efficient using vector representations and invariants of algebraic functions, how analogy and machine learning relate in natural language processing applications, and how far large language models can handle analogical relations.
*Illustrative imageMachine translation for low-resource languages
The lab targets languages for which little data is available. It studies data augmentation methods that improve model generalization and translation quality, as well as ways to improve the handling of low-resource languages by making use of analogical relations.
MembersFaculty
- ProfessorYves Lepage
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Rosetta Stone” Hans Hillewaert / CC BY-SA 4.0 (cropped)
- Research on analogical relations: “European Parliament languages” fdecomite / CC BY 2.0 (cropped)
- Machine translation for low-resource languages: “Diksionario ladino-serbo” Ikonija / CC BY-SA 3.0 (cropped)
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