Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network

Understand

Identification and extraction of singing voice from within musical mixtures is a key challenge in source separation and machine audition.

• Recently, deep neural networks (DNN) have been used to estimate 'ideal' binary masks for carefully controlled cocktail party speech separation problems.
• However, it is not yet known whether these methods are capable of generalizing to the discrimination of voice and non-voice in the context of musical mixtures.
• Here, we trained a convolutional DNN (of around a billion parameters) to provide probabilistic estimates of the ideal binary mask for separation of vocal sounds from real-world musical mixtures.