Audrey N. Tong, Lukasz L. Diduch, Jonathan G. Fiscus, Yasaman Haghpanah, Shudong Huang, David M. Joy, Kay Peterson, Ian M. Soboroff
Initiated in conjunction with DARPA's Low Resource Languages for Emergent Incidents (LORELEI) Program, the NIST LoReHLT (Low Re-source 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 and had its fi rst evaluation in July 2016. A total of eight teams out of 21 registrants participated in the evaluation over three tasks - machine translation, named entity recognition, and situation frame - in the surprise language Uyghur.
Machine Translation Special Issue NLP in Low Resource Languages
, Diduch, L.
, Fiscus, J.
, Haghpanah, Y.
, Huang, S.
, Joy, D.
, Peterson, K.
and Soboroff, I.
Overview of the NIST 2016 LoReHLT Evaluation, Machine Translation Special Issue NLP in Low Resource Languages, [online], https://doi.org/10.1007/s10590-017-9200-8
(Accessed December 4, 2023)