Transformer-based pretrained language models (T-PTLMs) have achieved great success in
almost every NLP task. The evolution of these models started with GPT and BERT. These …

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

The development of neural techniques has opened up new avenues for research in
machine translation. Today, neural machine translation (NMT) systems can leverage highly …

With the invention of deep learning concepts, Machine Translation (MT) migrated towards
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …

This paper proposes a novel direct Audio-Visual Speech to Audio-Visual Speech
Translation (AV2AV) framework where the input and output of the system are multimodal (ie …

We introduce Aksharantar, the largest publicly available transliteration dataset for 21 Indic
languages containing 26 million transliteration pairs. We build this dataset by mining …

In a multilingual country like India, automatic natural language translation plays a key role in
building a community with different linguistic people. Many researchers have explored and …

We explore the use of natural language prompts for controlling various aspects of the
outputs generated by machine translation models. We demonstrate that natural language …

Collecting labelled datasets for speech recognition systems for low-resource languages on
a diverse set of domains and speakers is expensive. In this work, we demonstrate an …

Transliteration is very important in the Indian language context due to the usage of multiple
scripts and the widespread use of romanized inputs. However, few training and evaluation …