1. A method implemented by at least one computing device, the method comprising: capturing, by the at least one computing device, temporal dependencies in sound data modeled through use of a recurrent neural network (RNN); extracting, by the at least one computing device, features from the sound data based on the captured temporal dependencies as a negative log-likelihood term of a nonnegative matrix factorization (NMF) cost using nonnegative matrix factorization (NMF); and performing, by the at least one computing device, one or more sound processing techniques on the sound data based at least in part on the extracted features.