activity
20192021
most citedWhat BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL2021★ 2 cited

What BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study

Ayush Kumar, Mukuntha Narayanan Sundararaman, Jithendra Vepa

Language Models (LMs) have been ubiquitously leveraged in various tasks including spoken language understanding (SLU). Spoken language requires careful understanding of speaker int…

eess.AS2021

Phoneme-BERT: Joint Language Modelling of Phoneme Sequence and ASR Transcript

Mukuntha Narayanan Sundararaman, Ayush Kumar, Jithendra Vepa

Recent years have witnessed significant improvement in ASR systems to recognize spoken utterances. However, it is still a challenging task for noisy and out-of-domain data, where s…

cs.CL2020

Tweet to News Conversion: An Investigation into Unsupervised Controllable Text Generation

Zishan Ahmad, Mukuntha N S, Asif Ekbal +1

Text generator systems have become extremely popular with the advent of recent deep learning models such as encoder-decoder. Controlling the information and style of the generated…

cs.CL2019

Sentiment-Aware Recommendation System for Healthcare using Social Media

Alan Aipe, Mukuntha Narayanan Sundararaman, Asif Ekbal

Over the last decade, health communities (known as forums) have evolved into platforms where more and more users share their medical experiences, thereby seeking guidance and inter…

cs.CV2019

Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection

Deepak Babu Sam, Skand Vishwanath Peri, Mukuntha Narayanan Sundararaman +2

We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm. Typical counting models predict crowd density for…