Bornil: An open-source sign language data crowdsourcing platform for AI enabled dialect-agnostic communication

TL;DR

Bornil is an open-source platform designed to facilitate multilingual sign language data collection, annotation, and validation, aiming to accelerate AI development for sign language recognition across dialects.

Contribution

It introduces a comprehensive crowdsourcing platform for sign language data, including collection, annotation, validation, and benchmarking, specifically applied to Bangladeshi Sign Language.

Findings

Largest Bangladeshi Sign Language dataset collected

Deep learning models achieved benchmark performance

Platform enables high-quality, dialect-agnostic sign language datasets

Abstract

The absence of annotated sign language datasets has hindered the development of sign language recognition and translation technologies. In this paper, we introduce Bornil; a crowdsource-friendly, multilingual sign language data collection, annotation, and validation platform. Bornil allows users to record sign language gestures and lets annotators perform sentence and gloss-level annotation. It also allows validators to make sure of the quality of both the recorded videos and the annotations through manual validation to develop high-quality datasets for deep learning-based Automatic Sign Language Recognition. To demonstrate the system's efficacy; we collected the largest sign language dataset for Bangladeshi Sign Language dialect, perform deep learning based Sign Language Recognition modeling, and report the benchmark performance. The Bornil platform, BornilDB v1.0 Dataset, and the codebases are available on https://bornil.bengali.ai