Instructions to use LyngualLabs/YorubaEnglish-CodeSwitching-TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- VoxCPM
How to use LyngualLabs/YorubaEnglish-CodeSwitching-TTS with VoxCPM:
import soundfile as sf from voxcpm import VoxCPM model = VoxCPM.from_pretrained("LyngualLabs/YorubaEnglish-CodeSwitching-TTS") wav = model.generate( text="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly expressive speech.", prompt_wav_path=None, # optional: path to a prompt speech for voice cloning prompt_text=None, # optional: reference text cfg_value=2.0, # LM guidance on LocDiT, higher for better adherence to the prompt, but maybe worse inference_timesteps=10, # LocDiT inference timesteps, higher for better result, lower for fast speed normalize=True, # enable external TN tool denoise=True, # enable external Denoise tool retry_badcase=True, # enable retrying mode for some bad cases (unstoppable) retry_badcase_max_times=3, # maximum retrying times retry_badcase_ratio_threshold=6.0, # maximum length restriction for bad case detection (simple but effective), it could be adjusted for slow pace speech ) sf.write("output.wav", wav, 16000) print("saved: output.wav") - Notebooks
- Google Colab
- Kaggle
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README.md
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| [DSN African Voices](https://www.africanvoices.
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| [NaijaVoices](https://huggingface.co/datasets/naijavoices/naijavoices-dataset) | 614.0 h | read + spontaneous, multi-speaker |
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| [YECS](https://lynguallabs.org/yecs) (LyngualLabs) | 107.5 h | Yoruba-English code-switching, 140 speakers |
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| [WAXAL](https://huggingface.co/datasets/google/WaxalNLP) (`yor_tts`) | 8.1 h | spontaneous |
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| Source | Hours | Notes |
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| [DSN African Voices](https://www.africanvoices.io) | 309.0 h | spontaneous, multi-speaker |
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| [NaijaVoices](https://huggingface.co/datasets/naijavoices/naijavoices-dataset) | 614.0 h | read + spontaneous, multi-speaker |
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| [YECS](https://lynguallabs.org/yecs) (LyngualLabs) | 107.5 h | Yoruba-English code-switching, 140 speakers |
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| [WAXAL](https://huggingface.co/datasets/google/WaxalNLP) (`yor_tts`) | 8.1 h | spontaneous |
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