Overview of the NIST 2016 LoReHLT evaluation
| Autor: | Shudong Huang, Audrey N. Tong, David Joy, Yasaman Haghpanah, Lukas Diduch, Kay Peterson, Jonathan G. Fiscus, Ian Soboroff |
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| Rok vydání: | 2017 |
| Předmět: |
Linguistics and Language
Computer science Low resource business.industry media_common.quotation_subject 02 engineering and technology computer.software_genre Language and Linguistics Conjunction (grammar) Surprise Named-entity recognition Artificial Intelligence Language technology 0202 electrical engineering electronic engineering information engineering NIST 020201 artificial intelligence & image processing Artificial intelligence Computational linguistics business computer Software Natural language processing media_common |
| Zdroj: | Machine Translation. 32:11-30 |
| ISSN: | 1573-0573 0922-6567 |
| DOI: | 10.1007/s10590-017-9200-8 |
| Popis: | Initiated in conjunction with DARPA’s low resource languages for emergent incidents (LORELEI) Program, the NIST LoReHLT (Low Resource Human Language Technology) evaluation series seeks to incubate research on fundamental natural language processing tasks in under-resourced languages. While part of the LORELEI program, LoReHLT is an open evaluation workshop that anyone may participate in, with its first evaluation taking place in July 2016. Eight teams, out of the 21 teams that registered, participated in the evaluation over three tasks—machine translation, named entity recognition, and situation frame—in the surprise language Uyghur. |
| Databáze: | OpenAIRE |
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