The First Swahili Language Scene Text Detection and Recognition Dataset
Fadila Wendigoundi Douamba, Jianjun Song, Ling Fu, Yuliang Liu and, Xiang Bai

TL;DR
This paper introduces the first publicly available Swahili scene text detection and recognition dataset, addressing a significant gap in low-resource language research and providing a benchmark for future studies.
Contribution
The authors created and publicly released the first Swahili scene text dataset, enabling research in a previously under-explored language for scene text recognition.
Findings
Dataset contains 976 images with word-level annotations.
Evaluated multiple scene text detection and recognition models on the dataset.
Provides a benchmark for Swahili scene text recognition research.
Abstract
Scene text recognition is essential in many applications, including automated translation, information retrieval, driving assistance, and enhancing accessibility for individuals with visual impairments. Much research has been done to improve the accuracy and performance of scene text detection and recognition models. However, most of this research has been conducted in the most common languages, English and Chinese. There is a significant gap in low-resource languages, especially the Swahili Language. Swahili is widely spoken in East African countries but is still an under-explored language in scene text recognition. No studies have been focused explicitly on Swahili natural scene text detection and recognition, and no dataset for Swahili language scene text detection and recognition is publicly available. We propose a comprehensive dataset of Swahili scene text images and evaluate the…
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Taxonomy
TopicsLanguage, Linguistics, Cultural Analysis · Handwritten Text Recognition Techniques · Natural Language Processing Techniques
