most citedNeural Machine Translation for the Indigenous Languages of the Americas: An Introduction

2 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

On the Automatic Generation and Simplification of Children's Stories

Maria Valentini, Jennifer Weber, Jesus Salcido +3

With recent advances in large language models (LLMs), the concept of automatically generating children's educational materials has become increasingly realistic. Working toward the…

cs.CL20232 cited

Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction

Manuel Mager, Rajat Bhatnagar, Graham Neubig +2

Neural models have drastically advanced state of the art for machine translation (MT) between high-resource languages. Traditionally, these models rely on large amounts of training…

cs.CL20231 cited

Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakers

Manuel Mager, Elisabeth Mager, Katharina Kann +1

In recent years machine translation has become very successful for high-resource language pairs. This has also sparked new interest in research on the automatic translation of low-…

cs.CL20231 cited

An Investigation of Noise in Morphological Inflection

Adam Wiemerslage, Changbing Yang, Garrett Nicolai +2

With a growing focus on morphological inflection systems for languages where high-quality data is scarce, training data noise is a serious but so far largely ignored concern. We ai…

cs.CL2023

Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models

Abteen Ebrahimi, Arya D. McCarthy, Arturo Oncevay +5

Large multilingual models have inspired a new class of word alignment methods, which work well for the model's pretraining languages. However, the languages most in need of automat…

cs.CL20171 cited

Neural Multi-Source Morphological Reinflection

Katharina Kann, Ryan Cotterell, Hinrich Schütze

We explore the task of multi-source morphological reinflection, which generalizes the standard, single-source version. The input consists of (i) a target tag and (ii) multiple pair…