Ewondo-ASR-Dataset

Ewondo-ASR-Dataset is a scripted speech dataset dedicated to the documentation and technological development of Ewondo (ISO 639-3: ewo), a Narrow Bantu language spoken primarily in the Centre, South and East Regions of Cameroon, where it also functions as a vehicular language. The dataset was compiled at the École Normale Supérieure de Yaoundé with contribution from students. The dataset comprises 1,781 high-quality MP3 audio recordings of Ewondo sentences read by 16 native speakers across 19 recording sessions, together with per-session sentence-to-audio mapping files enabling precise alignment between textual and acoustic data. Sentences were drawn from a scripted speech prompt list and read by each speaker in a controlled environment. The primary added value of this dataset lies in its orthographic alignment with the General Alphabet of Cameroon's Languages (AGLC; French acronym: AGLC — Alphabet Général des Langues Camerounaises), the reference standard for Cameroonian national languages. In particular, this dataset preserves systematic tone marking, a feature that the existing Common Voice Scripted Speech 25.0 – Ewondo dataset available on the Mozilla Data Collective platform tends to omit. By making tone information explicit in the transcription, this dataset enables the development and evaluation of speech technology models that are sensitive to the tonal contrasts that are phonemically contrastive in Ewondo. From a methodological perspective, the dataset is designed to complement the existing Common Voice Scripted Speech resource for Ewondo rather than to replace it, thereby extending the total amount of available Ewondo speech data aligned with an orthographically principled transcription standard. The parallel availability of AGLC-transcribed text and aligned speech makes the dataset suitable for a wide range of applications, including automatic speech recognition (ASR), text-to-speech (TTS), forced alignment, pronunciation modelling and language learning tools. It also directly supports efforts to standardise and normalise the digital representation of Ewondo in language technology contexts.