Learn about information extraction techniques for low-resource languages and their application in disaster response through the LORELEI project in this 41-minute lecture from CMU's Multilingual Natural Language Processing course. Explore methods, comparisons, and overall results while gaining insights into the challenges and opportunities in this field. Discover how multilingual NLP can be leveraged for critical real-world applications and understand the evaluation processes involved in such projects.
Overview
Syllabus
Introduction
Resources
DARPA
Lorelei
Deadlines
Evaluation Exercises
Collaborators
CMU
Methods
Comparison
Overall Results
Discussion Point
Taught by
Graham Neubig
Related Courses
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CMU Multilingual NLP - The LORELEI Project
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Information Extraction from Free Text Data in Health
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CMU Multilingual NLP 2020 - Text to Speech
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CMU Multilingual NLP 2020 - Low Resource ASR
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CMU Multilingual NLP 2020 - Multilingual Training and Cross-Lingual Transfer
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CMU Multilingual NLP: Language Contact and Similarity Across Languages
