Speech dereverberation and denoising using complex ratio masks

47 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction (2018, background): “However, recent studies along this line suggest that the patterns in the imaginary component are too random to predict [29], possibly because it is difficult for a learning machine to determine the sign of sin(∠Sc−∠X) only from energy-based features.”
Deep Learning for Environmentally Robust Speech Recognition (2017, background): “Both two phase-based masks were demonstrated to be more effective than normal IRMs in suppressing the reverberated noise in Williamson and Wang (2017b).”
Real-time Single-channel Dereverberation and Separation with Time-domain Audio Separation Network (2018, methodology): “Although there are methods such as phase-sensitive mask for separation [11] or complex ratio mask and iterative reconstruction for dereverberation [12, 7], the performance is still limited and model complexity might be much higher.”