hinglishNorm -- A Corpus of Hindi-English Code Mixed Sentences for Text Normalization

TL;DR

This paper introduces hinglishNorm, a publicly available annotated corpus of Hindi-English code-mixed sentences for text normalization, along with baseline normalization results demonstrating its utility.

Contribution

It is the first publicly available corpus of Hindi-English code-mixed sentences for text normalization and provides baseline normalization performance metrics.

Findings

Word Error Rate (WER) of 15.55

BLEU score of 71.2

METEOR score of 0.50

Abstract

We present hinglishNorm -- a human annotated corpus of Hindi-English code-mixed sentences for text normalization task. Each sentence in the corpus is aligned to its corresponding human annotated normalized form. To the best of our knowledge, there is no corpus of Hindi-English code-mixed sentences for text normalization task that is publicly available. Our work is the first attempt in this direction. The corpus contains 13494 parallel segments. Further, we present baseline normalization results on this corpus. We obtain a Word Error Rate (WER) of 15.55, BiLingual Evaluation Understudy (BLEU) score of 71.2, and Metric for Evaluation of Translation with Explicit ORdering (METEOR) score of 0.50.