The Makerere Radio Speech Corpus: A Luganda Radio Corpus for Automatic Speech Recognition

TL;DR

This paper introduces the Makerere Radio Speech Corpus, a 155-hour Luganda radio dataset, enabling development of automatic speech recognition systems for under-resourced languages in Africa.

Contribution

It presents the first publicly available Luganda radio speech dataset and baseline ASR performance results using open source tools.

Findings

First publicly available Luganda radio dataset

Baseline ASR performance established with Coqui STT

Supports development of ASR for under-resourced languages

Abstract

Building a usable radio monitoring automatic speech recognition (ASR) system is a challenging task for under-resourced languages and yet this is paramount in societies where radio is the main medium of public communication and discussions. Initial efforts by the United Nations in Uganda have proved how understanding the perceptions of rural people who are excluded from social media is important in national planning. However, these efforts are being challenged by the absence of transcribed speech datasets. In this paper, The Makerere Artificial Intelligence research lab releases a Luganda radio speech corpus of 155 hours. To our knowledge, this is the first publicly available radio dataset in sub-Saharan Africa. The paper describes the development of the voice corpus and presents baseline Luganda ASR performance results using Coqui STT toolkit, an open source speech recognition toolkit.