Neural machine translation: A review

F Stahlberg - Journal of Artificial Intelligence Research, 2020‏ - jair.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

Survey on reinforcement learning for language processing

V Uc-Cetina, N Navarro-Guerrero… - Artificial Intelligence …, 2023‏ - Springer
In recent years some researchers have explored the use of reinforcement learning (RL)
algorithms as key components in the solution of various natural language processing (NLP) …

Experts, errors, and context: A large-scale study of human evaluation for machine translation

M Freitag, G Foster, D Grangier, V Ratnakar… - Transactions of the …, 2021‏ - direct.mit.edu
Human evaluation of modern high-quality machine translation systems is a difficult problem,
and there is increasing evidence that inadequate evaluation procedures can lead to …

Hyporadise: An open baseline for generative speech recognition with large language models

C Chen, Y Hu, CHH Yang… - Advances in …, 2023‏ - proceedings.neurips.cc
Advancements in deep neural networks have allowed automatic speech recognition (ASR)
systems to attain human parity on several publicly available clean speech datasets …

Mass: Masked sequence to sequence pre-training for language generation

K Song, X Tan, T Qin, J Lu, TY Liu - arxiv preprint arxiv:1905.02450, 2019‏ - arxiv.org
Pre-training and fine-tuning, eg, BERT, have achieved great success in language
understanding by transferring knowledge from rich-resource pre-training task to the low/zero …

Findings of the 2019 conference on machine translation (WMT19)

L Barrault, O Bojar, MR Costa-Jussa, C Federmann… - 2019‏ - zora.uzh.ch
This paper presents the results of the premier shared task organized alongside the
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …

Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals

M Popel, M Tomkova, J Tomek, Ł Kaiser… - Nature …, 2020‏ - nature.com
The quality of human translation was long thought to be unattainable for computer
translation systems. In this study, we present a deep-learning system, CUBBITT, which …

Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond

M Artetxe, H Schwenk - … of the association for computational linguistics, 2019‏ - direct.mit.edu
We introduce an architecture to learn joint multilingual sentence representations for 93
languages, belonging to more than 30 different families and written in 28 different scripts …

Survey of low-resource machine translation

B Haddow, R Bawden, AVM Barone, J Helcl… - Computational …, 2022‏ - direct.mit.edu
We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

Simple, scalable adaptation for neural machine translation

A Bapna, N Arivazhagan, O Firat - arxiv preprint arxiv:1909.08478, 2019‏ - arxiv.org
Fine-tuning pre-trained Neural Machine Translation (NMT) models is the dominant approach
for adapting to new languages and domains. However, fine-tuning requires adapting and …