PEMO was originally developed to simulate psychoacoustical experiments like temporal or spectral masking experiments. Today's ASR systems, on the other hand, usually perform quite bad even in low noise. See the visual demonstration Recognition experiments were performed with PEMO feature extraction in a range of different setups. The robustness of the auditory-based preprocessing was compared with other front ends, with both HMM and neural network recognizers. The effect of additional monaural and binaural noise suppression prior to feature extraction was investigated.
Current research focusses on sub word unit recognition in noise.
Noise suppression based on neurophysiologically motivated SNR estimation for robust speech recognition', Proceedings of NIPS 2000, in press. 382-383, DEGA, Oldenburg. Combining Monaural Noise Reduction Algorithms and Perceptive Preprocessing for Robust Speech Recognition. A model of auditory perception as front end for automatic speech recognition. Auditory Feature Extraction and Recognizer Dependencies.