Voicefixer aims at the restoration of human speech regardless how serious its degraded
VoiceFixer
Voicefixer aims at the restoration of human speech regardless how serious its degraded. It can handle noise, reveberation, low resolution (2kHz~44.1kHz) and clipping (0.1-1.0 threshold) effect within one model.
Demo
Please visit demo page to view what voicefixer can do.
Usage
from voicefixer import VoiceFixer
voicefixer = VoiceFixer()
voicefixer.restore(input="", # input wav file path
output="", # output wav file path
cuda=False, # whether to use gpu acceleration
mode = 0) # You can try out mode 0, 1 to find out the best result
from voicefixer import Vocoder
# Universal Speaker Independent Vocoder
vocoder = Vocoder(sample_rate=44100) # only support 44100 sample rate
vocoder.oracle(fpath="", # input wav file path
out_path="") # output wav file path
Related Material
- Paper: Will be available before Oct.03.2021.
- Train & Evaluation pipline (Still working on it): https://github.com/haoheliu/voicefixer_main