Single-microphone blind channel identification in speech using spectrum classification
Nikolay D. Gaubitch, Mike Brookes, Patrick A. Naylor, Dushyant Sharma · 2011
We propose an algorithm for blind estimation of the magni-tude response of a channel using the observations of a single microphone. The algorithm employs channel robust RASTA filtered Mel-frequency cepstral coefficients as features and a Gaussian mixture model based classifier to generate a dictio-nary of average speech spectra. These are then used to infer the channel response from speech that has undergone spectral modification in the capturing process. Simulation results us-ing babble noise, car noise and white Gaussian noise are pre-sented, which demonstrate that the proposed method is able to estimate a variety of channel responses to within 3−4 dB in terms of weighted spectral distance; and it is more accurate than a previously published method. 1.