1 / 10

Multi-Engine MT for Quick MT

Multi-Engine MT for Quick MT. Missing Technology for Quick MT. NICE. LingWear. Core Rapid MT. - Multi-Engine MT - Omnivorous resource usage - Pervasive Machine Learning - Novel Approaches: * Max-Entropy models * Seeded Version Space Learning * Elicitation from native informants.

tiana
Download Presentation

Multi-Engine MT for Quick MT

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Multi-Engine MT for Quick MT

  2. Missing Technology for Quick MT NICE LingWear Core Rapid MT - Multi-Engine MT - Omnivorous resource usage - Pervasive Machine Learning - Novel Approaches: * Max-Entropy models * Seeded Version Space Learning * Elicitation from native informants ISI MT

  3. NICE Carnegie Mellon University April 12, 2000

  4. Project Members • Ralf Brown: MT • Jaime Carbonell: ML, MT • Alon Lavie: ML, MT • Lori Levin: Linguistics, MT • Rodolfo Vega: International and Development Education, Information Technology in Education (IT-EDU)

  5. Potential Collaborators • Chile: Universidad de la Frontera • Colombia: Ministry of Interior. (Ruth Connolly from OAS is looking into this.)

  6. Universidad de la Frontera • Instituto de Estudios Indigenas: Bilingual Multicultural Education Program • Instituto de Informatica Educativa: ENLACES Project, rural component • Both funded by the Ministry of Education

  7. Mineduc Programs in Chile Education Quality Improvement Program, MECE ENLACES Austral Region Zonal Center: Instituto de Informatica Educativa Bilingual Multicultural Education Program La Araucania Region Projects: Instituto de Estudios Indigenas

  8. Work in Year 1 • Establish partnerships • Collect data • First version of Example-Based MT between Spanish and one indigenous language • Develop elicitation corpus • Build elicitation interface

  9. Establishing Partnerships • Identify a community that wants to work with us: design an MT application that fits in with their plans for community development or bilingual or monolingual education • Identify scientists who want to work with us: linguists, computer scientists, etc. • Identify non-U.S. funding sources for the indigenous community and scientists. • Identify existing programs like ENLACES

  10. Work in Year 2 • Ongoing work from Year 1 • Experiment with version space learning of translation rules • Build a rule interpreter for running the translation rules

More Related