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License:
NOODL-1.0
Steward:
Institute of African Digital HumanitiesDataset ID:
cmk1bbz7o39v2mb07jjupvzud
Release Date: 1/5/2026
Format: MP3, TSV
Size: 19.25 MB
This dataset comprises a datasheet of Ewondo (Ewo) lexical entries collected in the speech area known as Mbida Mbani. Each entry is accompanied by illustrative sentences, word-by-word glosses and French translations. The resource is enriched with aligned audio recordings, making it suitable for linguistic analysis and speech technology development.
Licensing
Nwulite Obodo Open Data Licence 1.0 (NOODL-1.0)
https://licensingafricandatasets.com/nwulite-obodo-licenseRestrictions/Special Constraints
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Intended Use
(a) Speech-related tasks: - Automatic speech recognition (ASR): Audio–text alignment allows the evaluation of speech recognition models for Ewondo. However, I should be noted that the read sentences are transcribed phonetically. There is at least one competing orthographic standard for Ewondo; the General Alphabet of Cameroon's Languages is the one that is closest to phonetic transcription. The other is the Catholic Missionaries orthography inspired by the model laid out by François Pichon in 1950. - Text-to-speech (TTS): As the dataset contains clean sentence–audio pairs, it can also be used to evaluate speech synthesis or text-to-speech models. Here again, it should be noted that the alphabet used to write the sentences is the IPA alphabet and not the General Alphabet of Cameroon's Languages, the Protestant alphabet or the Catholic alphabet. - Speech–text alignment/forced alignment benchmarking: Fine-grained, word-level segmentation provides ideal ground truth for evaluating phoneme - or word-level aligners. | (b) Translation and multilingual tasks: - Machine translation (Ewondo ↔ French): The sentence-level alignment between Ewondo and French makes it a parallel corpus for evaluating translation models with the limitations of the employed phonetic orthographic standard. - Speech translation (speech-to-text): (c) Linguistic and lexicographic tasks - Morphological analysis/glossed corpus studies: The morpheme-level glosses are valuable for computational morphology, interlinear text modelling (ILTs) and grammar induction tasks. - Lexicon and part-of-speech tagging: These are useful for building linguistic resources such as dictionaries, morphological analysers or taggers for Ewondo.
Ewondo is a Narrow Bantu language which is indigenous to a population mainly located in the Centre Region of Cameroon, with pockets of settlements in the South, and East Regions. Ewondo is vehicular to populations in the South and East Regions of Cameroon, and has also developed into a creole known as Mongo Ewondo;
The term 'Ewondo' is used to describe a set of linguistic varieties whose speakers may or may not identify with the term. It is very difficult to determine with confidence, based on which variables, a particular linguistic variety can be categorised as Ewondo without distorting reality. For this reason, the author of this dataset has deemed it worthwhile to refer to the specific geographical locations or particular subgroups in which the data presented in this dataset was collected. This dataset was collected in the Mbida-Mbani subgroup, located southeast of Yaoundé primarily in the Nyong-et-Mfoumou and Nyong-et-So'o Divisions (around Akonolinga/Endom and Mbalmayo/Dzeng).
The writing system used for the transcription of Ewondo in this dataset is the International Phonetic Alphabet (IPA).
i, e, ɛ, a, ɔ, o, u, ə
b, d, dz, f, g, ɣ, h, k, l, m, mb, mf, mv, n, ɲ, ŋ, nd, ŋg, ŋk, ndz, r, p, s, t, ts, v, w, y, z
The datasheet shows lexical and grammatical contrastive tones, marked directly on vowels and sonorants:
The dataset was collected through a questionnaire that was designed to gather basic information about the Ewondo lexicon and grammar. This was done as part of the Atlas Linguistique du Cameroun (ALCAM) project.
The dataset represents a linguistic questionnaire designed to elicit the basic lexicon and grammatical information.
Total size is 19,25 MB
The dataset comprises: 1) a datasheet with 399 lines and 19 columns; 2) 378 voice clips read by a single female native speaker; 3) sentence-to-audio mapping with 383 lines and three columns.