3 citations · 4 across the 5 of their papers we have counts for
5 papers
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages
Vineet Bhat, Preethi Jyothi, Pushpak Bhattacharyya
Disfluency correction (DC) is the process of removing disfluent elements like fillers, repetitions and corrections from spoken utterances to create readable and interpretable text.…
Adversarial Training For Low-Resource Disfluency Correction
Vineet Bhat, Preethi Jyothi, Pushpak Bhattacharyya
Disfluencies commonly occur in conversational speech. Speech with disfluencies can result in noisy Automatic Speech Recognition (ASR) transcripts, which affects downstream tasks li…
DisfluencyFixer: A tool to enhance Language Learning through Speech To Speech Disfluency Correction
Vineet Bhat, Preethi Jyothi, Pushpak Bhattacharyya
Conversational speech often consists of deviations from the speech plan, producing disfluent utterances that affect downstream NLP tasks. Removing these disfluencies is necessary t…
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages
Shivam Mhaskar, Vineet Bhat, Akshay Batheja +3
In this work, we present our deployment-ready Speech-to-Speech Machine Translation (SSMT) system for English-Hindi, English-Marathi, and Hindi-Marathi language pairs. We develop th…
Multi-class Classifier based Failure Prediction with Artificial and Anonymous Training for Data Privacy
Dibakar Das, Vikram Seshasai, Vineet Sudhir Bhat +3
This paper proposes a novel non-intrusive system failure prediction technique using available information from developers and minimal information from raw logs (rather than mining…