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Outetts 0.1 350M
Overview :
OuteTTS-0.1-350M is a text-to-speech synthesis technology based on a pure language model, requiring no external adapters or complex architectures, achieving high-quality voice synthesis through carefully designed prompts and audio tokenization. This model is based on the LLaMa architecture, utilizing 350 million parameters to demonstrate the potential for direct voice synthesis using language models. It processes audio in three steps: using WavTokenizer for audio tokenization, creating precise word-to-audio mappings through CTC forced alignment, and generating structured prompts that follow specific formats. The key advantages of OuteTTS include a pure language modeling approach, voice cloning capabilities, and compatibility with llama.cpp and GGUF formats.
Target Users :
The target audience comprises developers and enterprises requiring high-quality voice synthesis technology, such as those involved in voice assistants, audiobooks, and automated news broadcasting. OuteTTS-0.1-350M simplifies the voice synthesis process through a pure language model approach, lowering technical barriers and enabling more developers and businesses to leverage this technology to enhance productivity and user experience.
Use Cases
Developers use OuteTTS-0.1-350M to provide natural and smooth voice outputs for voice assistants.
Audiobook producers utilize this model to convert text content into high-quality audiobooks.
News agencies employ OuteTTS-0.1-350M to automatically convert press releases into broadcast-quality speech.
Features
Text-to-speech synthesis achieved through a pure language modeling approach.
Voice cloning capability that allows the creation of speech outputs with specific voice characteristics.
Based on the LLaMa architecture, utilizing a model with 350 million parameters.
Compatibility with llama.cpp and GGUF formats for easy integration and use.
Precise voice synthesis enabled through audio tokenization and CTC forced alignment.
Structured prompts improve the accuracy and naturalness of voice synthesis.
Efficient voice synthesis for short sentences; long texts must be segmented for processing.
How to Use
1. Install OuteTTS: Install the outetts library via pip.
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2. Initialize the interface: Choose between using the Hugging Face model or the GGUF model and initialize the interface.
3. Generate voice: Input text and set relevant parameters such as temperature and repetition penalty, then call the interface to generate voice.
4. Play voice: Utilize the playback feature of the interface to directly play the generated voice.
5. Save voice: Save the generated voice as a file, such as in WAV format.
6. Voice cloning: Create a custom speaker and use that voice to generate speech.
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