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

10/18/2020
by   Piyush Makhija, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/20/2020

PHINC: A Parallel Hinglish Social Media Code-Mixed Corpus for Machine Translation

Code-mixing is the phenomenon of using more than one language in a sente...
research
04/08/2021

User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization

Morphological analysis (MA) and lexical normalization (LN) are both impo...
research
05/25/2020

Dialect Text Normalization to Normative Standard Finnish

We compare different LSTMs and transformer models in terms of their effe...
research
05/19/2021

Detection of Emotions in Hindi-English Code Mixed Text Data

In recent times, we have seen an increased use of text chat for communic...
research
10/21/2022

CEFR-Based Sentence Difficulty Annotation and Assessment

Controllable text simplification is a crucial assistive technique for la...
research
06/08/2017

The Algorithmic Inflection of Russian and Generation of Grammatically Correct Text

We present a deterministic algorithm for Russian inflection. This algori...
research
11/11/2020

The Impact of Text Presentation on Translator Performance

Widely used computer-aided translation (CAT) tools divide documents into...

Please sign up or login with your details

Forgot password? Click here to reset