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KittenTTS is an open-source, ultra-lightweight, and high-quality text-to-speech model featuring just 15 million parameters and a binary size under 25 MB. It is designed for real-time CPU-based deployment across diverse platforms. Ultra-lightweight, model size less than 25MB. CPU-optimized, runs without GPU on any device. High-quality voices, several premium voice options available. Fast inference, optimized for real-time speech synthesis.
Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles
...For those who only need synthesis, the project is published as a Python library (pip install style-bert-vits2) and can run on CPU without an NVIDIA GPU, though training still requires GPU hardware.
Bangla text to speech
Multilingual (Bangla, English) real-time ([almost] in a GPU) speech synthesis library.
Installation
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* Install Anaconda
* conda create -n new_virtual_env python==3.6.8
* conda activate new_virtual_env
* pip install -r requirements.txt
* While running for the first time, keep your internet connection on to download the weights of the speech synthesis models (>500 MB)
* For fast inference, you must install tensorflow-gpu and have a NVidia GPU.
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