In speech recognition, spectro-temporal feature extraction and the training of the acoustical model are usually performed separately. To improve recognition performance, we present a combined model which allows the training of the feature extraction filters along with a neural net classifier. Besides expecting that this joint training will result in a better recognition performance, we also exp...

We seek to explore computational approaches for audition that are inspired by computational visual neuroscience. In particular, we seek to leverage recent progress over the past few years in building a biologically-faithful hierarchical, feed-forward system for visual object recognition [13,14]. The system, which was designed to closely match the currently known feed-forward path in the ventral...

In speech recognition, feature extraction and acoustical model training are traditionally done in two separate steps. Here, instead, we use a framework that combines spectro-temporal feature extraction and the training of neural network based acoustic models into a single process. We found earlier that this approach can be successfully applied for the recognition of speech. In this paper, we pr...

A two-stage singing voice separation algorithm using spectrotemporal modulation features is proposed in this paper. First, music clips are transformed into auditory spectrograms and the spectral-temporal modulation contents of all time-frequency (T-F) units of the auditory spectrograms are extracted using an auditory model. Then, T-F units are sequentially clustered using the expectation-maximi...

We previously developed noise robust Hierarchical SpectroTemporal (HIST) speech features. The learning of the features was performed in an unsupervised way with unlabeled speech data. In a final stage we deployed Principal Component Analysis (PCA) to reduce the feature dimensions and to diagonalize them. In this paper we investigate if a discriminant projection can further increase the performa...

Receptive fields of single units in the auditory midbrain of anesthetized rats were studied using random FM-tone stimuli of narrow frequency-ranges. Peri-spike averaging of the modulating waveform first produced a spectro-temporal receptive field (STRF). Combining STRFs obtained from the same unit at different frequency regions generated a composite receptive field covering a wider frequency ra...

In order to enhance automatic speech recognition performance in adverse conditions, Gabor features motivated by physiological measurements in the primary auditory cortex were optimized and evaluated. In the Aurora 2 experimental setup such localized, spectro-temporal filters combined with a Tandem system yield robust performance with a feature set size of 30. Improved results can be obtained wh...