This is a simplified guide to an AI model called Parler-Tts maintained by Cjwbw. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model overview
parler-tts is a lightweight text-to-speech (TTS) model developed by cjwbw, a creator at Replicate. It is trained on 10.5K hours of audio data and can generate high-quality, natural-sounding speech with controllable features like gender, background noise, speaking rate, pitch, and reverberation. parler-tts is related to models like voicecraft, whisper, and sabuhi-model, which also focus on speech-related tasks. Additionally, the parler_tts_mini_v0.1 model provides a lightweight version of the parler-tts system.
Model inputs and outputs
The parler-tts model takes two main inputs: a text prompt and a text description. The prompt is the text to be converted into speech, while the description provides additional details to control the characteristics of the generated audio, such as the speaker's gender, pitch, speaking rate, and environmental factors.
Inputs
- Prompt: The text to be converted into speech.
- Description: A text description that provides details about the desired characteristics of the generated audio, such as the speaker's gender, pitch, speaking rate, and environmental factors.
Outputs
- Audio: The generated audio file in WAV format, which can be played back or further processed as needed.
Capabilities
The parler-tts model can generate hi...
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