Machine learning has been heavily researched and widely used in many disciplines.
However, achieving high accuracy requires a large amount of data that is sometimes …

Despite the many proposals to solve the neural machine translation (NMT) problem of low-
resource languages, it continues to be difficult. The issue becomes even more complicated …

Image captioning is an important task for improving human-computer interaction as well as
for a deeper understanding of the mechanisms underlying the image description by human …

One important issue that affects the performance of neural machine translation is the scale of
available parallel data. For low-resource languages, the amount of parallel data is not …

Low-resource languages often face the problem of insufficient data, which leads to poor
quality in machine translation. One approach to address this issue is data augmentation …

Data augmentation is crucial for enhancing the performance of text classification models
when labelled training data are scarce. For natural language processing (NLP) tasks, large …

The Zhuang ethnic minority in China possesses its own ethnic language and no ethnic
script. Cultural exchange and transmission encounter hurdles as the Zhuang rely exclusively …

Featured Application The application of this research is to create better multilingual datasets
by utilizing the insights gained from our investigation into mBART and XLM-Roberta. These …

The integration of digital voice assistants in nursing residences is becoming increasingly
important to facilitate nursing productivity with documentation. A key idea behind this system …

Cantonese-English is a low-resource language pair for machine translation (MT) studies,
despite the vast amount of English content publicly available online and the large amount of …