5 papers
Get away with less: Need of source side data curation to build parallel corpus for low resource Machine Translation
Saumitra Yadav, Manish Shrivastava
Data curation is a critical yet under-researched step in the machine translation training paradigm. To train translation systems, data acquisition relies primarily on human transla…
Segmentation Beyond Defaults: Asymmetrical Byte Pair Encoding for Optimal Machine Translation Performance
Saumitra Yadav, Manish Shrivastava
Existing Machine Translation (MT) research often suggests a single, fixed set of hyperparameters for word segmentation models, symmetric Byte Pair Encoding (BPE), which applies the…
TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu
Gopichand Kanumolu, Lokesh Madasu, Nirmal Surange +1
News headline generation is a crucial task in increasing productivity for both the readers and producers of news. This task can easily be aided by automated News headline-generatio…
Unsupervised Approach to Evaluate Sentence-Level Fluency: Do We Really Need Reference?
Gopichand Kanumolu, Lokesh Madasu, Pavan Baswani +2
Fluency is a crucial goal of all Natural Language Generation (NLG) systems. Widely used automatic evaluation metrics fall short in capturing the fluency of machine-generated text.…
Mukhyansh: A Headline Generation Dataset for Indic Languages
Lokesh Madasu, Gopichand Kanumolu, Nirmal Surange +1
The task of headline generation within the realm of Natural Language Processing (NLP) holds immense significance, as it strives to distill the true essence of textual content into…