Search Results for "projects/b2n-sprout"

...The project targets both power users and beginners: Windows users without Git or Python can install and run it using bundled .bat scripts, while advanced users can work with virtual environments, uv, and Python tooling. It includes a full GUI editor to script dialogue, set different styles per line, edit dictionaries, and save/load projects, plus a separate web UI and Colab notebooks for training and experimentation. 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.

...You will never miss if someone talks to you. Voice cloning can be accomplished with Coqui in less than five minutes without GPU. The result is archived and can be used the next time in game. Some TTS projects already started to add tag support to speak text with emotions or sing it. If a game designer has that in mind with a good chat log she can voiced her game over night. reads the log and sends new chat text to piper. ~/.config/Epic/PSUnreal/Saved/Logs/Pongo_Donjo_chat.txt If a line number is set it can speak all the chat text and waits for new chat text. ...

...The toolkit is organized with example experiments (“egs”) and visualization demos that guide users through training, evaluation, and inspection of models. Built on the broader OpenMMLab ecosystem, Amphion follows modular design patterns and configuration systems similar to other OpenMMLab projects, easing adoption for users who are already familiar with that stack.

MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English. The codebase is implemented in Python (with PyTorch) and includes modules for encoder, synthesizer, vocoder, preprocessing, and inference, as well as demo scripts and a web-server interface for easier experimentation or deployment. ...

VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that...