Deep Learning implementation of DAE + VAE
Separate noisy audio into clean speaker tracks
Separate mixed audio into two distinct sounds
Split audio on silence and stream chunks
Clean up noisy images using kNN denoising
Separate audio from video and remove silence
Convert text to speech with background music
Remove noise from images
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Remove background from images
Remove noise from images
remove image background
Proyect1 DAE VAE is a deep learning implementation that combines Denoting Autoencoder (DAE) and Variational Autoencoder (VAE) to achieve powerful audio processing capabilities. Primarily designed to remove background noise from audio, it also leverages its advanced architecture to generate new audio content. This tool is ideal for tasks requiring noise reduction and audio generation, making it a versatile solution for both audio cleaning and creative applications.
What file formats does Proyect1 DAE VAE support?
Proyect1 DAE VAE supports common audio formats like WAV, MP3, and AAC. For image processing, it supports PNG, JPEG, and BMP.
How does the noise reduction work?
The DAE component identifies and removes background noise by learning the underlying patterns in the audio data, ensuring minimal loss of important information.
Can I use Proyect1 DAE VAE for both audio and image processing?
Yes, while its primary focus is audio, the tool also supports image denoising and generation through its VAE architecture.