52 citations · 109 across the 6 of their papers we have counts for
4 papers · 1 filter
Towards Building ASR Systems for the Next Billion Users
Tahir Javed, Sumanth Doddapaneni, Abhigyan Raman +5
Recent methods in speech and language technology pretrain very LARGE models which are fine-tuned for specific tasks. However, the benefits of such LARGE models are often limited to…
SuperShaper: Task-Agnostic Super Pre-training of BERT Models with Variable Hidden Dimensions
Vinod Ganesan, Gowtham Ramesh, Pratyush Kumar
Task-agnostic pre-training followed by task-specific fine-tuning is a default approach to train NLU models. Such models need to be deployed on devices across the cloud and the edge…
A Primer on Pretrained Multilingual Language Models
Sumanth Doddapaneni, Gowtham Ramesh, Mitesh M. Khapra +2
Multilingual Language Models (\MLLMs) such as mBERT, XLM, XLM-R, \textit{etc.} have emerged as a viable option for bringing the power of pretraining to a large number of languages.…
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages
Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj +15
We present Samanantar, the largest publicly available parallel corpora collection for Indic languages. The collection contains a total of 49.7 million sentence pairs between Englis…