77 citations · 319 across the 61 of their papers we have counts for
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IndicMT Eval: A Dataset to Meta-Evaluate Machine Translation metrics for Indian Languages
Ananya B. Sai, Vignesh Nagarajan, Tanay Dixit +4
The rapid growth of machine translation (MT) systems has necessitated comprehensive studies to meta-evaluate evaluation metrics being used, which enables a better selection of metr…
MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation
Dominik Macháček, Ondřej Bojar, Raj Dabre
There have been several meta-evaluation studies on the correlation between human ratings and offline machine translation (MT) evaluation metrics such as BLEU, chrF2, BertScore and…
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Zhuoyuan Mao, Chenhui Chu, Raj Dabre +3
Word alignment has proven to benefit many-to-many neural machine translation (NMT). However, high-quality ground-truth bilingual dictionaries were used for pre-editing in previous…
Fusion of Self-supervised Learned Models for MOS Prediction
Zhengdong Yang, Wangjin Zhou, Chenhui Chu +4
We participated in the mean opinion score (MOS) prediction challenge, 2022. This challenge aims to predict MOS scores of synthetic speech on two tracks, the main track and a more c…
IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages
Aman Kumar, Himani Shrotriya, Prachi Sahu +6
Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages. In this paper, we present the IndicNLG Benchmark, a collecti…