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Convtasnet Libri3Mix Sepnoisy 8k
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Convtasnet Libri3Mix Sepnoisy 8k

Developed by JorisCos
A ConvTasNet model trained based on the Asteroid framework, designed to separate 3 independent audio sources from mixed audio, specifically optimized for noisy speech data at 8kHz sampling rate.
Sound Separation
PyTorch
#Multi-speaker separation#Low sample rate audio processing#Noisy scenario enhancement
Downloads 33
Release Time : 3/2/2022

Model Overview

This model adopts the ConvTasNet architecture, specifically designed for audio source separation tasks, capable of separating 3 independent speech sources from mixed audio, especially suitable for speech separation in noisy environments.

Model Features

Multi-source speech separation
Capable of simultaneously separating 3 independent speech sources from mixed audio
Noise robustness
Specifically optimized for speech separation in noisy environments
Lightweight architecture
Utilizes the efficient ConvTasNet architecture, suitable for real-time processing

Model Capabilities

Audio source separation
Noise suppression
Multi-speaker separation

Use Cases

Speech processing
Meeting recording enhancement
Separating clear speech of individual speakers from recordings with multiple people speaking simultaneously
Can improve speech recognition accuracy
Audio post-production
Extracting specific speaker voices from mixed audio tracks
Facilitates remixing or editing
Assistive technology
Hearing aids
Separating target speaker speech in noisy environments
Improves auditory experience for users with hearing impairments
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