ClearerVoice-Studio

Why we included this project

Audio that reaches a speech model is rarely clean. ClearerVoice-Studio bundles pretrained models and scripts for the usual clean-up jobs: suppressing background noise, separating overlapping speakers, restoring bandwidth or resolution on degraded recordings, and extracting a target speaker from a busy track. The core package installs with pip, and models accept and return raw NumPy arrays, so it slots into existing Python training or inference code without routing everything through a GUI. Researchers get retraining and fine-tuning scripts plus utilities for generating noisy or noisy-reverberant training data, while practitioners can try the hosted demos before settling on a model. It is a practical shortcut when you want proven speech processing without stitching the algorithms together yourself.