This is the Linux app named VoiceFixer whose latest release can be downloaded as voicefixer-0.0.12.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named VoiceFixer with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS:
VoiceFixer
DESCRIPTION:
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 reconstructs a high-quality waveform from those features. Unlike many single-purpose noise reduction tools, VoiceFixer targets a “general speech restoration” problem (GSR), capable of handling multiple types of distortions at once, which makes it suitable for old recordings, phone-call audio, amateur voice recordings, or archival media. Evaluations show that VoiceFixer significantly improves both objective and subjective audio quality compared to baseline speech-enhancement methods.
Features
- General speech restoration (GSR) capable of handling noise, clipping, low bitrate, reverberation, and other distortions simultaneously
- Two-stage pipeline: analysis (denoising/cleaning) plus neural vocoder-based synthesis for high-fidelity waveform reconstruction
- Full-bandwidth restoration — can reconstruct high-quality audio even from low-resolution inputs
- Works on severely degraded real-world recordings — historical speech, phone calls, amateur audio
- Model provided with code — easy to integrate into custom audio pipelines or projects
- Significant perceptual quality improvement over classic single-task enhancement systems
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/voicefixer.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.