An open-source GPU-accelerated feature extraction tool

An extraction of feature-vectors from speech audio signal is a computationally intensive task. However, MFCC and PLP features remain the most popular for more than a decade. We made a GPU-accelerated implementation of the feature extraction processing. The implementation produces identical features as the reference Hidden Markov Toolkit (HTK) but in a fraction of the elapsed time. The saved time can be invested elsewhere and thus it can speed-up research. The implementation was developed in CUDA which supports NVidia GPUs only. So, we added an Open-CL implementation to support any current GPU. The project is an open-source package, thus research community can modify or adapt the implementation to their needs.