Environment Classification via Blind Roomprints Estimation

In this paper we present a novel approach for environment classification for speech recordings, which does not require the selection of decaying reverberation tails. It is based on a multi-band RT60 analysis of blind channel estimates and achieves an accuracy of up to 93.8% on test recordings derived from the ACE corpus.