3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CL2023
APE-then-QE: Correcting then Filtering Pseudo Parallel Corpora for MT Training Data Creation
Akshay Batheja, Sourabh Deoghare, Diptesh Kanojia +1
Automatic Post-Editing (APE) is the task of automatically identifying and correcting errors in the Machine Translation (MT) outputs. We propose a repair-filter-use methodology that…
cs.CL2023
"A Little is Enough": Few-Shot Quality Estimation based Corpus Filtering improves Machine Translation
Akshay Batheja, Pushpak Bhattacharyya
Quality Estimation (QE) is the task of evaluating the quality of a translation when reference translation is not available. The goal of QE aligns with the task of corpus filtering,…
cs.CL2023★ 3 cited
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…