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

<h1 style="text-align: center;">Abstract</h1>
<p> 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.</p><br>


## 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](https://lingo.iitgn.ac.in/)
- **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"
}  
```