FBEM: A filter bank EM algorithm for the joint optimization of features and acoustic model parameters in bird call classification

This paper extends the expectation-maximization (EM) algorithm to estimate not only optimal acoustic model parameters, but also optimal center frequencies and bandwidths of the filter bank used in cepstral feature extraction for bird call classification. The search is done using the gradient ascent method. Filter bank and model parameters are optimized iteratively. Experiments are conducted on a large noisy corpus containing Antbird calls from 5 species. It is shown that features extracted using the optimized filter bank result in a lower classification error rate than those extracted using a Melscaled filter bank.