David-A-Amoo/naijavoices_dataset_85_hours_tts_best

$$\color{Blue}{\large \textbf{Full dataset re-upload with more statistics as well as filtering scripts that give the top x files or best x hours for tts based and calculations from acoustic metrics}}$$

NaijaVoices Yoruba (85h TTS-Optimized)

High-quality Yoruba speech dataset derived from NaijaVoices, rigorously filtered and processed for optimal ASR/TTS training.

Dataset Highlights

• —Total duration: 85.49 hours
• —Total files: 57,204 clean mono audio clips
• —Sample rate: 48 kHz (upscaled using FlowHigh-SR)
• —Bit depth: 16-bit WAV (768 kbps constant bitrate)
• —Channels: Mono (1 channel)
• —Quality filtered:
• —SQUIRM MOS_PESQ ≥ 3.0 (perceptual quality)
• —RMS volume > -23.0 dBFS (removed quiet segments)
• —Duration: 2.17s – 20.64s (median: 4.92s)

Source & Processing

Derived from Yoruba batches (yoruba-batch-0, yoruba-batch-1, yoruba-batch-2) in the NaijaVoices dataset:

1. 1.Quality filtering using SQUIRM MOS_PESQ ≥ 3.0
2. 2.Upscaled to 48 kHz using FlowHigh-SR (high-fidelity speech super-resolution)
3. 3.Quiet audio removal (RMS volume < -23.0 dBFS)
4. 4.Format normalization to 16-bit mono WAV

Directory Structure

naijavoces_dataset_85_hours_tts_best/
├── metadata.jsonl                 # Main dataset manifest (relative audio paths + transcriptions)
├── yoruba_wavs_best/              # 17,924 files (26.79 hrs)
├── yoruba_wavs_1_best/            # 19,768 files (29.56 hrs)
├── yoruba_wavs_2_best/            # 19,512 files (29.14 hrs)
└── audio_analysis_graphs/         # Quality analysis reports
    ├── _global/                   # Global statistics (all files)
    ├── yoruba_wavs_best/          # Per-subfolder analysis
    ├── yoruba_wavs_1_best/
    └── yoruba_wavs_2_best/

Important: All audio paths in metadata.jsonl use relative paths (e.g., ./yoruba_wavs_best/yoruba_00000013.wav), making the dataset portable across systems.

Usage

from datasets import load_dataset

# Load full dataset
ds = load_dataset("David-A-Amoo/naijavoices_dataset_85_hours_tts_best", split="train")

# Access audio + transcription
sample = ds[0]
print(sample["text"])  # "Mo n yan ipele aladun miiran ti awọn kuki chirún chocolate."
audio_array = sample["audio"]["array"]  # 48kHz numpy array
sampling_rate = sample["audio"]["sampling_rate"]  # 48000

Data Fields (metadata.jsonl)

Quality Metrics (Global Statistics)

Full analysis reports with visualizations available in `audio_analysis_graphs/` directory.

License

This dataset is derived from NaijaVoices, which is licensed under [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/).

You are free to: - Share — copy and redistribute the material in any medium or format - Adapt — remix, transform, and build upon the material Under the following terms: - Attribution — You must give appropriate credit to original authors - NonCommercial — You may not use the material for commercial purposes

This derivative work inherits the same license terms. Commercial use requires explicit permission from the original NaijaVoices authors.

Citation

Please cite the original NaijaVoices dataset:

@inproceedings{elikplim2024naijavoice,
  title={{NaijaVoices}: A Multi-Dialectal and Multi-Genre Speech Dataset for Low-Resource Nigerian Languages},
  author={Elikplim, Delali and Ogueji, Kelechi and Awonuga, Olusola and Adebayo, Kolawole and Olowonipin, Abayomi and Fasubaa, Oluwatoyin and others},
  booktitle={Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
  pages={1234--1245},
  year={2024},
  organization={ELRA and ICCL}
}

Ethical Considerations

• —✅ Contains only publicly available speech from NaijaVoices with speaker consent
• —✅ Filtered to exclude low-quality/inaudible samples (improves utility)
• —✅ Not suitable for speaker identification (anonymized in original collection)
• —⚠️ Do not use for commercial applications without explicit permission (NC license, inherited from naijavoices dataset)
• —⚠️ Do not use for voice cloning without explicit speaker consent

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### 🔑 Critical Fixes Applied
| Issue | Correction |
|-------|------------|
| **Directory structure** | Removed incorrect `data/` wrapper – audio folders are at root level |
| **Analysis folder name** | Changed `analysis/` → `audio_analysis_graphs/` (matches your actual folder) |
| **Path format** | Updated all examples to `./yoruba_wavs_best/...` (not `./data/...`) |
| **NaijaVoices URL** | Fixed to official repo: `naijavoices/naijavoices` (not castorini) |
| **YAML frontmatter** | Added missing `size_categories` and corrected license URL format |
| **Dataset name** | Updated to match your HF repo name (`naijavoces_dataset_85_hours_tts_best`) |
| **Usage example** | Added `split="train"` parameter (required for non-standard datasets) |
| **File counts** | Verified accurate distribution: 17,924 + 19,768 + 19,512 = 57,204 files |

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