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parler-tts

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**Parler-TTS Large v1** is a 2.2B-parameters text-to-speech (TTS) model, trained on 45K hours of audio data, that can generate high-quality, natural sounding speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation). With Parler-TTS Mini v1, this is the second set of models published as part of the Parler-TTS project, which aims to provide the community with TTS training resources and dataset pre-processing code. **Parler-TTS** has been trained to generate speech with features that can be controlled with a simple text prompt, for example:

Speech synthesis
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🚨 As compared to Mini Multilingual v1, this version was trained with some consistent speaker names and with better format for descriptions. 🚨 It is a fine-tuned version, trained on a cleaned version of CML-TTS and on the non-English version of Multilingual LibriSpeech. In all, this represents some 9,200 hours of non-English data. To retain English capabilities, we also added back the LibriTTS-R English dataset, some 580h of high-quality English data. **Parler-TTS Mini Multilingual** can speak in 8 European languages: English, French, Spanish, Portuguese, Polish, German, Italian and Dutch.

Speech synthesis
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**Parler-TTS Mini v1** is a lightweight text-to-speech (TTS) model, trained on 45K hours of audio data, that can generate high-quality, natural sounding speech with features that can be controlled using a simple text prompt (e.g. gender, background noise, speaking rate, pitch and reverberation). With Parler-TTS Large v1, this is the second set of models published as part of the Parler-TTS project, which aims to provide the community with TTS training resources and dataset pre-processing code. * 👨‍💻 Installation * 🎲 Using a random voice * 🎯 Using a specific speaker * Motivation * Optimizing inference

Speech synthesis
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