Search Results for "compact"

...It focuses on making audiobook creation easy and fast: from a single command, the tool splits an e-book into chapters, synthesizes audio for each section, and then merges the results into a structured audiobook with chapter-based WAV files and a final .m4b container. The Kokoro-82M model it uses is compact (82M parameters) yet natural sounding, trained on under 100 hours of audio, and supports multiple languages, including English (US/UK), Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese. Audiblez can run entirely from the command line via a PyPI package or through a simple cross-platform GUI built on wxPython, giving both advanced users and non-technical users an accessible workflow.

Fish Speech is a state-of-the-art open-source text-to-speech project that has evolved into the OpenAudio series of advanced TTS models. The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong...

...It is built with a focus on privacy and simplicity, offering a streamlined three-step workflow: Extract, Edit, and Convert. Key Features: Neural Quality TTS: Uses the compact yet powerful Kokoro-82M model for high-fidelity, expressive voice synthesis. Privacy-First & Offline: After a one-time initial model download, all processing happens on your CPU. Your books never leave your computer. Multi-Language Support: Curated voices for English (US & UK), Italian, French, Spanish, and Portuguese (BR). ...

WaveRNN is a PyTorch implementation of DeepMind’s WaveRNN vocoder, bundled with a Tacotron-style TTS front end to form a complete text-to-speech stack. As a vocoder, WaveRNN models raw audio with a compact recurrent neural network that can generate high-quality waveforms more efficiently than many traditional autoregressive models. The repository includes scripts and code for preprocessing datasets such as LJSpeech, training Tacotron to produce mel spectrograms, training WaveRNN on those spectrograms (with optional GTA data), and finally generating audio. ...