text stringlengths 5 119 | audio dict |
|---|---|
Lé mí wɛ yi nyamɔn nyɛ ŋ mɔnŋujemɛ | {"array":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.(...TRUNCATED) |
Kpɔnnɔ ŋ du kpoŋu aŋu | {"array":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.(...TRUNCATED) |
ŋ kpɔ mɔ́ wɔ ale hunnɔ | {"array":[0.0,-0.000030517578125,-0.0001220703125,-0.00030517578125,-0.00054931640625,-0.00091552734(...TRUNCATED) |
Tom can Marie can, wowo dele bɔbɔ lɔ mɛ ò | {"array":[0.0,-0.0001220703125,-0.000335693359375,-0.00079345703125,-0.001434326171875,-0.0023193359(...TRUNCATED) |
Zili le dɔmɛzi nuxu xo ɔ̀ | {"array":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.(...TRUNCATED) |
Le enu jɔjɔ lɔo yi ɔ do yi dɔ yi wo xo nuxu ahan | {"array":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.(...TRUNCATED) |
ŋ bumɔ́ wɔ a kpɔɛ alo wɔ a nya | {"array":[0.0,0.0,-0.00006103515625,-0.0001220703125,-0.000244140625,-0.000396728515625,-0.000640869(...TRUNCATED) |
ŋ ɖu nyidin ŋuɖuɖu fɛn du | {"array":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.(...TRUNCATED) |
Eshi vɔ le anyi nuŋlwɛ ci mɛ | {"array":[0.0,0.0,0.0,0.0,-0.000030517578125,-0.00006103515625,-0.000091552734375,-0.0001220703125,-(...TRUNCATED) |
Na yi ji anyi hún kpɔ | {"array":[0.0,-0.000030517578125,-0.0001220703125,-0.00030517578125,-0.000579833984375,-0.0009765625(...TRUNCATED) |
Adja Speech Dataset for ASR and TTS
This is the canonical public Adja speech dataset for the May 2026 thesis release. It is intended for automatic speech recognition, text-to-speech, and speech pipeline experiments.
Components
adja_speech_orpheus_48khz
This component duplicates the Orpheus speech source from JosueG/adja-tts-orpheus.
The source repository is treated as read-only provenance; this dataset repo is
the public canonical release surface.
The component is useful for ASR because each row pairs Adja text with speech, and useful for TTS because the same pairs can train or evaluate speech synthesis models.
Release split policy:
- No new train/dev/test split is created for the public dataset.
- The full Orpheus corpus is published as the single Hugging Face
trainpartition because that is the source dataset shape.
HF partition:
train: 1,597 rows
Schema:
text: normalized transcription textaudio: speech audio stored from the Orpheus source at 48 kHz
Provenance And Quality Note
The processed derivative JosueG/adja-tts-mms-ready is not used as the
canonical public source after release review found bad/noisy playback on
Hugging Face. This repo goes back to the Orpheus source data instead.
No existing experiment dependency repo is renamed, moved, or edited by this release.
Related Thesis Artifacts
- Code and result archive:
FrejusGdm/cs-thesis-may-2026 - Existing canonical MT dataset:
JosueG/french-adja-parallel-corpus
Citation
If you use this dataset, cite:
Josue Godeme. 2026. CS Thesis May 2026: French-Adja MT and Adja Speech Experiments.
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