Results 11 to 20 of about 4,220,052 (297)

Automatic evaluation of the quality of machine translation of a scientific text: the results of a five-year-long experiment [PDF]

open access: yesE3S Web of Conferences, 2021
We report on various approaches to automatic evaluation of machine translation quality and describe three widely used methods. These methods, i.e. methods based on string matching and n-gram models, make it possible to compare the quality of machine ...
Ulitkin Ilya   +3 more
doaj   +1 more source

Towards Making the Most of ChatGPT for Machine Translation [PDF]

open access: yesConference on Empirical Methods in Natural Language Processing, 2023
ChatGPT shows remarkable capabilities for machine translation (MT). Several prior studies have shown that it achieves comparable results to commercial systems for high-resource languages, but lags behind in complex tasks, e.g., low-resource and distant ...
Keqin Peng   +7 more
semanticscholar   +1 more source

Survey of Mongolian-Chinese Neural Machine Translation [PDF]

open access: yesJisuanji kexue, 2022
Machine translation is the process of using a computer to convert one language into another language.With the deep understanding of semantics,neural machine translation has become the most mainstream machine translation method at present,and it has made ...
HOU Hong-xu, SUN Shuo, WU Nier
doaj   +1 more source

Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis [PDF]

open access: yesNAACL-HLT, 2023
Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions: 1) How well do ...
Wenhao Zhu   +7 more
semanticscholar   +1 more source

Document-Level Machine Translation with Large Language Models [PDF]

open access: yesConference on Empirical Methods in Natural Language Processing, 2023
Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks.
Longyue Wang   +6 more
semanticscholar   +1 more source

Adaptive Machine Translation with Large Language Models [PDF]

open access: yesEuropean Association for Machine Translation Conferences/Workshops, 2023
Consistency is a key requirement of high-quality translation. It is especially important to adhere to pre-approved terminology and adapt to corrected translations in domain-specific projects.
Yasmin Moslem, Rejwanul Haque, Andy Way
semanticscholar   +1 more source

A Survey on Hybrid Machine Translation [PDF]

open access: yesE3S Web of Conferences, 2020
Machine translation has gradually developed in past 1940’s.It has gained more and more attention because of effective and efficient nature. As it makes the translation automatically without the involvement of human efforts. The distinct models of machine
Anugu Anusha, Ramesh Gajula
doaj   +1 more source

Neural Machine Translation of Rare Words with Subword Units [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2015
Neural machine translation (NMT) models typically operate with a fixed vocabulary, but translation is an open-vocabulary problem. Previous work addresses the translation of out-of-vocabulary words by backing off to a dictionary.
Rico Sennrich   +2 more
semanticscholar   +1 more source

Multilingual Denoising Pre-training for Neural Machine Translation [PDF]

open access: yesTransactions of the Association for Computational Linguistics, 2020
This paper demonstrates that multilingual denoising pre-training produces significant performance gains across a wide variety of machine translation (MT) tasks.
Yinhan Liu   +7 more
semanticscholar   +1 more source

The Flores-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation [PDF]

open access: yesTransactions of the Association for Computational Linguistics, 2021
One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks. Current evaluation benchmarks either lack good coverage of low-resource languages, consider only restricted ...
Naman Goyal   +9 more
semanticscholar   +1 more source

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