metadata

license: cc-by-4.0
task_categories:
  - translation
language:
  - hi
  - en
tags:
  - code-mixing
  - code-switching
  - NLG
size_categories:
  - 1K<n<10K

Abstract

Text generation is a highly active area of research in the computational linguistic community. The evaluation of the generated text is a challenging task and multiple theories and metrics have been proposed over the years. Unfortunately, text generation and evaluation are relatively understudied due to the scarcity of high-quality resources in code-mixed languages where the words and phrases from multiple languages are mixed in a single utterance of text and speech. To address this challenge, we present a corpus (HinGE) for a widely popular code-mixed language Hinglish (code-mixing of Hindi and English languages). HinGE has Hinglish sentences generated by humans as well as two rule-based algorithms corresponding to the parallel Hindi-English sentences. In addition, we demonstrate the in- efficacy of widely-used evaluation metrics on the code-mixed data. The HinGE dataset will facilitate the progress of natural language generation research in code-mixed languages.

Dataset Details

HinGE: A Dataset for Generation and Evaluation of Code-Mixed Hinglish Text is a high-quality Hindi-English code-mixed dataset for the NLG tasks, manually annotated by five annotators.

The dataset contains the following columns:

A. English, Hindi: The parallel source sentences from the IITB English-Hindi parallel corpus.
B. Human-generated Hinglish: A list of Hinglish sentences generated by the human annotators.
C. WAC: Hinglish sentence generated by the WAC algorithm (see paper for more details).
D. WAC rating1, WAC rating2: Quality rating to the Hinglish sentence generated by the WAC algorithm. The quality rating ranges from 1-10.
E. PAC: Hinglish sentence generated by the PAC algorithm (see paper for more details).
F. PAC rating1, PAC rating2: Quality rating to the Hinglish sentence generated by the PAC algorithm. The quality rating ranges from 1-10.

Dataset Description

Curated by: Lingo Research Group at IIT Gandhinagar
Language(s) (NLP): Bilingual (Hindi [hi], English [en])
Licensed by: cc-by-4.0

Citation

If you use this dataset, please cite the following work:

@inproceedings{srivastava-singh-2021-hinge,
    title = "{H}in{GE}: A Dataset for Generation and Evaluation of Code-Mixed {H}inglish Text",
    author = "Srivastava, Vivek  and
      Singh, Mayank",
    booktitle = "Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.eval4nlp-1.20/",
    doi = "10.18653/v1/2021.eval4nlp-1.20"
}