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+ ---
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+ language:
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+ - rw
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+ pipeline_tag: text-to-speech
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+ license: cc
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+ tags:
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+ - TTS
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+ - Kinyarwanda
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+ - Text to speech
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+ ---
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+
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+
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+
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+ ## Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+ This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture.
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+
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+
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+ # Usage
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+ Install the Coqui's TTS library:
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+ ```
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+ pip install git+https://github.com/coqui-ai/TTS@0910cb76bcd85df56bf43654bb31427647cdfd0d#egg=TTS
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+ ```
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+ Download the files from this repo, then run:
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+
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+ ```
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+ tts --text "text" --model_path model.pth --encoder_path SE_checkpoint.pth.tar --encoder_config_path config_se.json --config_path config.json --speakers_file_path speakers.pth --speaker_wav conditioning_audio.wav --out_path out.wav
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+ ```
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+ Where the conditioning audio is a wav file(s) to condition a multi-speaker TTS model with a Speaker Encoder, you can give multiple file paths. The d_vectors is computed as their average.
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+ # References
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+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information should go in this section. -->
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+ [1] [YourTTS paper](https://arxiv.org/pdf/2112.02418.pdf)
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+ [2] [Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model] (https://openreview.net/pdf?id=1gLgrqWnHF)