BAAD: A Multipurpose Dataset for Automatic Bangla Offensive Speech Recognition

Published: 25 July 2022| Version 2 | DOI: 10.17632/w24g8xn23c.2
Contributors:
Al Abid Supto,
Zannat Chowdhury,
Hana Sultan Chowdhury,
Md Fahad Hossain

Description

This dataset contains audio data of common abusive Bengali words. The audio data includes 114 slang words with 5277 audio clips by 60 native speakers who participated, speaking in various dialects from over 20 districts. The recorded audio data is natively recorded by the participants in .WAV format. • This dataset can be used to develop an automatic Bengali Slang Speech Recognition System, and also as a benchmark for new ML models. • This dataset can potentially help minimize cyberbully victims and children exposed to abusive remarks on video/audio content containing abusive language. In addition, this dataset of carefully collected offensive language in Bengali aims to work towards achieving this goal. • 65% of the participants were male and 35% were female. • 10 university students participated in the evaluation of this dataset. • This dataset can be further enriched, and some background noise in the dataset can be useful to simulate a more real world scenario, if desired, which otherwise could be removed. ***Warning: this dataset contains audio content that may be disturbing or upsetting. ***

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Categories

Artificial Intelligence, Natural Language Processing, Speech Recognition

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