Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …

Data Augmentation (DA) methods–a family of techniques designed for synthetic generation
of training data–have shown remarkable results in various Deep Learning and Machine …

The goal of automatic Sign Language Production (SLP) is to translate spoken language to a
continuous stream of sign language video at a level comparable to a human translator. If this …

We present sentence aligned parallel corpora across 10 Indian Languages-Hindi, Telugu,
Tamil, Malayalam, Gujarati, Urdu, Bengali, Oriya, Marathi, Punjabi, and English-many of …

Context-aware neural machine translation (NMT) is a promising direction to improve the
translation quality by making use of the additional context, eg, document-level translation, or …

It is of great value to answer product questions based on heterogeneous information
sources available on web product pages, eg, semi-structured attributes, text descriptions …

The success of AI models relies on the availability of large, diverse, and high-quality
datasets, which can be challenging to obtain due to data scarcity, privacy concerns, and …

Abstract Machine translation is one of the applications of natural language processing which
has been explored in different languages. Recently researchers started paying attention …

Abstract Multi-Hop Question Answering (MHQA) is a significant area in question answering,
requiring multiple reasoning components, including document retrieval, supporting sentence …