Zobrazeno 1 - 10
of 2 338
pro vyhledávání: '"Neural machine translation"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 7, Pp 1725-1747 (2024)
Machine translation (MT) is the process of using a computer to convert one language into another language with the same semantics. With the introduction of neural network, neural machine translation (NMT), as a powerful machine translation technology
Externí odkaz:
https://doaj.org/article/a083e771857f4d9eb89120b9e4cfa9e5
Publikováno v:
International Journal of Mathematical, Engineering and Management Sciences, Vol 9, Iss 5, Pp 1067-1088 (2024)
Neural machine translation (NMT) approaches driven by artificial intelligence (AI) has gained more and more attention in recent years, mainly due to their simplicity yet state-of-the-art performance. Despite NMT models with attention mechanism relyin
Externí odkaz:
https://doaj.org/article/8b4cbf9c6c60438588518cb75c813067
Publikováno v:
Revista de Llengua i Dret - Journal of Language and Law, Pp 88-105 (2024)
Training neural machine translation systems with noisy data has been shown to improve robustness (Heigold et al., 2018). The objective of the present study is to test Google Translate and DeepL performance in the detection and correction of typograph
Externí odkaz:
https://doaj.org/article/073e76fa738448739a8d65b6788744c7
Autor:
Rongshu Wang, Jianhua Chen
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-21 (2024)
Abstract Backgrounds The single-pass long reads generated by third-generation sequencing technology exhibit a higher error rate. However, the circular consensus sequencing (CCS) produces shorter reads. Thus, it is effective to manage the error rate o
Externí odkaz:
https://doaj.org/article/b19ea2e0103a419fb0b21a3b09276794
Autor:
Md Saef Ullah Miah, Md Mohsin Kabir, Talha Bin Sarwar, Mejdl Safran, Sultan Alfarhood, M. F. Mridha
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Sentiment analysis is an essential task in natural language processing that involves identifying a text’s polarity, whether it expresses positive, negative, or neutral sentiments. With the growth of social media and the Internet, sentiment
Externí odkaz:
https://doaj.org/article/5f1bae8808354ba5bf7ccef3f10b103d
Publikováno v:
PeerJ Computer Science, Vol 10, p e2122 (2024)
Grammar error correction systems are pivotal in the field of natural language processing (NLP), with a primary focus on identifying and correcting the grammatical integrity of written text. This is crucial for both language learning and formal commun
Externí odkaz:
https://doaj.org/article/70ba51a5dabb4847925168235172bbe6
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 3, Pp 731-739 (2024)
In recent years, neural network models such as Transformer have achieved significant success in machine translation. However, training these models relies on rich labeled data, posing a challenge for low-resource machine translation due to the limite
Externí odkaz:
https://doaj.org/article/7bb12dc88d284b96a3a9110b17d02869
Publikováno v:
Vietnam Journal of Computer Science, Vol 11, Iss 01, Pp 75-94 (2024)
Domain adaptation in neural machine translation (NMT) tasks often involves working with datasets that have a different distribution from the training data. In such scenarios, k-nearest-neighbor machine translation (kNN-MT) has been shown to be effect
Externí odkaz:
https://doaj.org/article/31b9a746dfe045c9a1ddf6a8ce556961
Autor:
Murun Yang
Publikováno v:
IEEE Access, Vol 12, Pp 124695-124704 (2024)
Unlike general translation, constrained translation necessitates the proper use of predefined restrictions, such as specific terminologies and entities, during the translation process. However, current neural machine translation (NMT) models exhibit
Externí odkaz:
https://doaj.org/article/ee9e2f2fbd484321bd1356f765fd94d0
Publikováno v:
Cadernos de Tradução, Vol 44, Iss esp. 1 (2024)
It is common knowledge that the publication of translation projects carried out by students is a very motivating factor for training. Since the second semester of 2015-2016, undergraduate translation students of the Faculty of Arts and Humanities of
Externí odkaz:
https://doaj.org/article/a2c57a0a05e64a33ab4f5fc7cdb3b4b9