other · Zenodo (CERN European Organization for Nuclear Research)
A dedicated dataset comprising spoken audio recordings in the Mooré language has been compiled and released for research and educational use. These recordings were collected specifically to aid the development and preliminary evaluation of a voice-centred mobile application intended for English language learning in Burkina Faso. The dataset underpins a closed-vocabulary speech-recognition component within the software. Structurally, this recognition system is built upon Mel-frequency cepstral coefficient features and bidirectional long short-term memory models. By capturing regional spoken input, the resource provides the necessary acoustic data to build, train, and assess specialised language-learning interfaces tailored to Mooré speakers.
Digital language-learning tools require localized acoustic data to function effectively for speakers of indigenous languages. By offering voice recordings in Mooré, this dataset helps developers construct and assess voice-driven educational mobile applications tailored specifically to language learners in Burkina Faso.
This dataset enables the development of voice-driven mobile tools tailored for Mooré speakers learning English. The intended end users are language learners in Burkina Faso. Regarding technology readiness, the system is at an applied and tested stage, having already supported the prototype development and preliminary evaluation of a closed-vocabulary mobile application.
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This dataset contains Mooré speech recordings collected and used for the development and preliminary evaluation of a voice-centered mobile application for English language learning in Burkina Faso. The recordings support a closed-vocabulary speech-recognition component based on MFCC features and BiLSTM models. The dataset is provided for research and educational purposes.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.5281/zenodo.22403548
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