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Dereverberation is often performed directly on the reverberant audio signal,without knowledge of the acoustic environment. Reverberation time, T60,however, is an essential acoustic factor that reflects how reverberation mayimpact a signal. In this work, we propose to perform dereverberation whileleveraging key acoustic information from the environment. More specifically, wedevelop a joint learning approach that uses a composite T60 module and aseparate dereverberation module to simultaneously perform reverberation timeestimation and dereverberation. The reverberation time module provides keyfeatures to the dereverberation module during fine tuning. We evaluate ourapproach in simulated and real environments, and compare against severalapproaches. The results show that this composite framework improves performancein environments.

A Composite T60 Regression and Classification Approach for Speech Dereverberation