Language technology into high schools for revitalization of endangered languages

Caballero, Luis Camacho; Zevallos, Rodolfo

doi:10.1109/intercon50315.2020.9220197

Cited by 1 publication

(1 citation statement)

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“…While there are exceptions such as the European low-resource projects Horizon 1 and others, smaller countries with less governmental power like Peru, for example, provide less funding in general. (Camacho and Zevallos, 2020) Demand is focused on high-resource languages which have more speakers with more buying power. Nonetheless, with the introduction of large-language models (LLMs), interest by larger private companies like Meta (Costajussà et al, 2022) in LRMT has increased.…”

Section: Minimum Viable Product (Mvp): Minimal Requirementsmentioning

confidence: 99%

A Research-Based Guide for the Creation and Deployment of a Low-Resource Machine Translation System

Ortega,

Church

2023

Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Proce

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The machine translation (MT) field seems to focus heavily on English and other high-resource languages. Though, low-resource MT (LRMT) is receiving more attention than in the past. Successful LRMT systems (LRMTS) should make a compelling business case in terms of demand, cost and quality in order to be viable for end users. When used by communities where lowresource languages are spoken, LRMT quality should not only be determined by the use of traditional metrics like BLEU, but it should also take into account other factors in order to be inclusive and not risk overall rejection by the community. MT systems based on neural methods tend to perform better with high volumes of training data, but they may be unrealistic and even harmful for LRMT. It is obvious that for research purposes, the development and creation of LRMTS is necessary. However, in this article, we argue that two main workarounds could be considered by companies that are considering deployment of LRMTS in the wild: human-in-the-loop and sub-domains.

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Section: Minimum Viable Product (Mvp): Minimal Requirementsmentioning

confidence: 99%