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License:
NOODL-1.0
Steward:
Institute of African Digital HumanitiesDataset ID:
cmrbac56k00lbmm070txylq42
Release Date: 7/7/2026
Format: WAV, TSV
Size: 1.04 GB
Eton-TTS-Dataset is a single-speaker scripted speech dataset dedicated to the documentation and technological development of Eton (ISO 639-3: eto), a Narrow Bantu language spoken primarily in the Centre Region of Cameroon. The dataset was compiled at the École Normale Supérieure de Yaoundé in the framework of the Mozilla Data Collective (2026). The dataset comprises 1,802 audio clips of Eton sentences read by a single native female speaker across 19 recording sessions (2026-06-18 to 2026-07-01), one per source text, together with per-session sentence-to-audio mapping files enabling precise alignment between textual and acoustic data. Sentences were drawn from the same scripted speech prompt list used for the companion Eton-ASR-Dataset and read in a controlled environment by one consistent voice, which is the design requirement for training or fine-tuning corpus-based TTS voice models. As with the companion Eton-ASR-Dataset, 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, the dataset preserves systematic tone marking, a feature that the existing Common Voice Scripted Speech 25.0 – Eton 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 synthesis models that are sensitive to the tonal contrasts that are phonemically contrastive in Eton. From a methodological perspective, this dataset complements the multi-speaker Eton-ASR-Dataset: while the latter is intended for ASR robustness across speakers, Eton-TTS-Dataset provides a single consistent voice reading near-complete coverage of the same 19-text prompt list (1,802 of the available scripted sentences), making it directly suited to building a single-voice Eton TTS system aligned with AGLC orthography and tone marking.
Licensing
Nwulite Obodo Open Data Licence 1.0 (NOODL-1.0)
https://licensingafricandatasets.com/nwulite-obodo-licenseRestrictions/Special Constraints
By downloading this dataset, you agree:
Forbidden Usage
You agree not to use the data for: determining the identity of the speaker in the dataset; attempting to clone the voice or train models that imitate the speaker in this dataset outside of the intended TTS research use agreed with the legal owner; Generative AI misuse; reproduction; duplication; modification; augmentation; copying; distribution; transmission; display; sale; transfer; publication or creation of derivative works without the explicit permission of the legal owner of the dataset.
Intended Use
(a) Speech-related tasks: - Text-to-speech (TTS): A single consistent voice reading near-complete coverage of the scripted prompt list makes this dataset directly suited to training or fine-tuning a corpus-based Eton TTS voice model. The AGLC orthographic standard, including tone diacritics, should be taken into account when designing TTS experiments. - Automatic speech recognition (ASR): Audio–text alignment also enables single-speaker evaluation of speech recognition models for Eton, complementing the multi-speaker Eton-ASR-Dataset. Sentences are transcribed in AGLC with full tone marking, suited for tone-aware ASR models. - Speech–text alignment / forced alignment benchmarking: Fine-grained audio–text pairing provides ground truth for evaluating phoneme- or word-level aligners adapted to tonal Bantu languages. (b) Linguistic and lexicographic tasks: - Phonological and tonal analysis: The systematic tone notation in AGLC orthography makes the dataset suitable for studying tonal alternations, downstep, floating tones and other phonological phenomena in Eton, as realised by a single speaker. - Orthographic standardisation and normalisation: The dataset can serve as a reference corpus for evaluating and training text normalisation and grapheme-to-phoneme (G2P) models aligned with the AGLC standard. - Language documentation: The dataset contributes to the digital documentation of Eton scripted speech in AGLC orthography, extending the existing Common Voice and Eton-ASR-Dataset resources with a single-voice, orthographically principled TTS corpus.
Eton (ISO 639-3: eto) is a Narrow Bantu language belonging to the Beti-Fang group of the Benue-Congo branch. It is indigenous to a population located primarily in the Lekié Division, Centre administrative region, Cameroon. Eton is closely related to Ewondo and other Beti-Fang languages such as Bulu, Ntumu and Fang. Ethnologue estimates the number of speakers at approximately 120,000. Despite its linguistic significance as a Beti-Fang variety, Eton remains significantly underrepresented in language technology resources.
The sociolinguistic situation of Eton, including its internal varieties/dialects, is not entirely resolved in mainstream research. However, two varieties stand out as the most salient, at least in public discourse: the Okola variety and the Obala variety.
The present dataset was recorded by a single speaker who originates from Okola. The speaker acknowledges that the text she read reflects a mix of both the Okola and Obala varieties.
The writing system used for the transcription of Eton in this dataset is the General Alphabet of Cameroon's Languages (AGLC), as adopted by the Ministry of Basic Education of Cameroon and regularly updated by the Direction de la Promotion des Langues Nationales. The AGLC provides a phonologically motivated orthographic standard for Cameroonian national languages and serves as the reference framework for Eton literacy materials.
The vowel system attested in the dataset includes the following oral vowels:
a, e, ə, i, o, u, ɔ
Long vowels are represented by vowel doubling (e.g. aa, ee, oo).
The consonant inventory reflected in the dataset includes simple, prenasalized and digraph consonants:
b, d, dz, f, g, gb, h, k, kp, l, m, mb, mv, n, nd, ng, nk, nz, ny, ŋ, p, s, t, ts, v, w, y, z
Special symbols: ə (mid central vowel), ŋ (velar nasal), gb and kp (labial-velar consonants)
Eton is a tonal language with lexical and grammatical contrastive tones. The dataset employs systematic tone marking on vowels in accordance with the AGLC convention:
Unmarked vowels represent tonally neutral or contextually determined syllables. This explicit tone notation distinguishes the present dataset from the Common Voice Scripted Speech 25.0 – Eton resource, in which tone diacritics are systematically absent.
The dataset was compiled from the same scripted speech prompt lists used for the Eton-ASR-Dataset, read by a single native speaker of Eton in recording sessions held at the École Normale Supérieure de Yaoundé between 2026-06-18 and 2026-07-01, in the framework of the Mozilla Data Collective project. Sentences were transcribed in accordance with the AGLC orthographic standard, with full tone marking.
The dataset represents scripted speech in Eton, covering a broad range of everyday sentence types drawn from a general-purpose ASR/TTS prompt list. All utterances are scripted rather than spontaneous, read by a single consistent voice.
Total audio duration: 15,315 seconds (04:15:15), distributed across 1,802 audio clips in 19 recording sessions, all contributed by a single native female speaker of Eton.
The dataset comprises:
1,802 audio clips (1,797 WAV + 5 WebM) read by a single native female speaker of Eton, with a total duration of 15,315 seconds (04:15:15), distributed across 19 recording sessions, one per source text:
Nineteen per-session sentence-to-audio mapping files (mapping.tsv), each with 4 columns.
| audio file | sentence (Eton, AGLC) |
|---|---|
| b463ea04bee572197ceea5ca91164821.wav | Ǹkoməní bídí ígibətɛn bə́ tə lɔŋɔ nâ masi ó tə ceni á mínnam minnam. |
| 58e609852f7fc689ceb9ce50a6ad8ee2.wav | Á ńnam ígíbətɛn, bídí bə́ tə lɔ́ŋɔ nâ masi bí nə̂ m̀bámə́na olɛ́s, ká í lom e bicidəga. |
| ccda4f52c04b0b763f20034d73d33d8f.wav | Tuugán mɔ íbás ásu waani á mbús iso asú, bə́ŋ nala, ósúsúá ná miní boŋəbo e alú, e miná yə yén ńnyəbəní ítə itə́ ámos ó tə to! |
| edfc470aeb48b42e00713859a6173757.wav | Bán ńkɔ̌l á sí ású ná ó gbê evɔ́g á zə́zə. |