This repository contains data that has been scraped from a video lectures website called the Spoken Tutorial Project which can be found at https://spoken-tutorial.org/
If you find this data useful in your research please cite the following paper:
@inproceedings{gupta-etal-2021-training,
title = "Training Data Augmentation for Code-Mixed Translation",
author = "Gupta, Abhirut and
Vavre, Aditya and
Sarawagi, Sunita",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.459",
pages = "5760--5766",
abstract = "Machine translation of user-generated code-mixed inputs to English is of crucial importance in applications like web search and targeted advertising. We address the scarcity of parallel training data for training such models by designing a strategy of converting existing non-code-mixed parallel data sources to code-mixed parallel data. We present an m-BERT based procedure whose core learnable component is a ternary sequence labeling model, that can be trained with a limited code-mixed corpus alone. We show a 5.8 point increase in BLEU on heavily code-mixed sentences by training a translation model using our data augmentation strategy on an Hindi-English code-mixed translation task.",
}