In this era of online meetings, background noise removal systems are really essential for effective workflow. This project is a model that suppresses background noise.
Nowadays, online meetings, online schooling, and work-from-home methodologies are being used extensively due to the COVID-19 pandemic! Despite the success of this "online-X", the factors of domestication and lack of professional work environment may introduce a potential barrier and can hinder the establishment of an effective workflow. We often observe annoying background noises at the speaker's end which adds up to the noise. Hence, to avoid this "STUPID BACKGROUND NOISE" a robust system could be implemented which can suppress the background noise giving the ideal results. This project aims to provide the solution for the above-discussed problem using a deep learning approach!
With the help of Convolutional Autoencoders, this model is trained to detect the unwanted noise in the audio samples.
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