L3Cube-HingCorpus and HingBERT: A Code Mixed Hindi-English Dataset and BERT Language Models

Abstract

Code-switching occurs when more than one language is mixed in a given sentence or a conversation. This phenomenon is more prominent on social media platforms and its adoption is increasing over time. Therefore code-mixed NLP has been extensively studied in the literature. As pre-trained transformer-based architectures are gaining popularity, we observe that real code-mixing data are scarce to pre-train large language models. We present L3Cube-HingCorpus, the first large-scale real Hindi-English code mixed data in a Roman script. It consists of 52.93M sentences and 1.04B tokens, scraped from Twitter. We further present HingBERT, HingMBERT, HingRoBERTa, and HingGPT. The BERT models have been pre-trained on codemixed HingCorpus using masked language modelling objectives. We show the effectiveness of these BERT models on the subsequent downstream tasks like code-mixed sentiment analysis, POS tagging, NER, and LID from the GLUECoS benchmark. The HingGPT is a GPT2 based generative transformer model capable of generating full tweets. We also release L3Cube-HingLID Corpus, the largest code-mixed Hindi-English language identification(LID) dataset and HingBERT-LID, a production-quality LID model to facilitate capturing of more code-mixed data using the process outlined in this work. The dataset and models are available at https://github.com/l3cubepune/code-mixed-nlp.

My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks

“…Chakravarthi et al ( 2021) and have released datasets encompassing Tamil-English and Malayalam-English code-mixed texts. Nayak and Joshi (2022) have made available Hing-Corpus, a Hindi-English code-mix dataset, and also open-sourced pre-trained models trained on codemix corpora. Srivastava and Singh (2021) provide HinGE, a dataset for the generation and evaluation of code-mixed Hinglish text, and demonstrate techniques for algorithmically creating synthetic Hindi code-mixed texts.…”

MUTANT: A Multi-sentential Code-mixed Hinglish Dataset

“…We annotate the words in A using a code-mixed language identification tool. Specifically, we use L3Cube-HingLID (Nayak and Joshi, 2022) for this task. A word w i ∈ A can take either of the three language tags from the set {English, Hindi, Other}.…”