A voyage on neural machine translation for Indic languages
With the invention of deep learning concepts, Machine Translation (MT) migrated towards
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …
A survey on low-resource neural machine translation
Neural approaches have achieved state-of-the-art accuracy on machine translation but
suffer from the high cost of collecting large scale parallel data. Thus, a lot of research has …
suffer from the high cost of collecting large scale parallel data. Thus, a lot of research has …
Sparse co-attention visual question answering networks based on thresholds
Z Guo, D Han - Applied Intelligence, 2023 - Springer
Most existing visual question answering (VQA) models choose to model the dense
interactions between each image region and each question word when learning the co …
interactions between each image region and each question word when learning the co …
Knowledge distillation for multilingual unsupervised neural machine translation
Unsupervised neural machine translation (UNMT) has recently achieved remarkable results
for several language pairs. However, it can only translate between a single language pair …
for several language pairs. However, it can only translate between a single language pair …
A spatial–temporal graph model for pronunciation feature prediction of Chinese poetry
Q Wang, W Liu, X Wang, X Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of artificial intelligence, speech recognition and prediction have
become one of the important research domains with wild applications, such as intelligent …
become one of the important research domains with wild applications, such as intelligent …
SJTU-NICT's Supervised and Unsupervised Neural Machine Translation Systems for the WMT20 News Translation Task
In this paper, we introduced our joint team SJTU-NICT's participation in the WMT 2020
machine translation shared task. In this shared task, we participated in four translation …
machine translation shared task. In this shared task, we participated in four translation …
Optimization of English machine translation by deep neural network under artificial intelligence
X Guo - Computational Intelligence and Neuroscience, 2022 - Wiley Online Library
To improve the function of machine translation to adapt to global language translation, the
work takes deep neural network (DNN) as the basic theory, carries out transfer learning and …
work takes deep neural network (DNN) as the basic theory, carries out transfer learning and …
Neural machine translation for Kashmiri to English and Hindi using pre-trained embeddings
SK Sheshadri, D Gupta… - 2022 OITS International …, 2022 - ieeexplore.ieee.org
Neural Machine Translation (NMT) is one of the advanced approaches of Machine
Translation (MT) that has recently gained popularity. A significant amount of parallel corpus …
Translation (MT) that has recently gained popularity. A significant amount of parallel corpus …
Unsupervised hyperspectral and multispectral images fusion based on the cycle consistency
Hyperspectral images (HSI) with abundant spectral information reflected materials property
usually perform low spatial resolution due to the hardware limits. Meanwhile, multispectral …
usually perform low spatial resolution due to the hardware limits. Meanwhile, multispectral …
Obscurity-quantified curriculum learning for machine translation evaluation
The pre-trained language model has been developed for evaluating the quality of machine
translation. It achieves state-of-the-art results. However, building a model for the evaluation …
translation. It achieves state-of-the-art results. However, building a model for the evaluation …