Phoneme Classification Using Temporal Tracking of Speech Clusters in Spectro-temporal Domain

Bioinspired sparse spectro-temporal representation of speech for robust classification

In this work, a first approach to a robust phoneme recognition task by means of a biologically-inspired feature extraction method is presented. The proposed technique provides an approximation to the speech signal representation at the auditory cortical level. It is based on an optimal dictionary of atoms, estimated from auditory spectrograms, and the Matching Pursuit algorithm to approximate t...

Spectro-temporal Modulations for Robust Speech Emotion Recognition Spectro-temporal Modulations for Robust Speech Emotion Recognition

Aging and Spectro-Temporal Integration of Speech

The purpose of this study was to determine the effects of age on the spectro-temporal integration of speech. The hypothesis was that the integration of speech fragments distributed over frequency, time, and ear of presentation is reduced in older listeners-even for those with good audiometric hearing. Younger, middle-aged, and older listeners (10 per group) with good audiometric hearing partici...

Spectro-temporal analysis of speech using 2-d Gabor filters

We present a 2-D spectro-temporal Gabor filterbank based on the 2-D Fast Fourier Transform, and show how it may be used to analyze localized patches of a spectrogram. We argue that the 2-D Gabor filterbank has the capacity to decompose a patch into its underlying dominant spectro-temporal components, and we illustrate the response of our filterbank to different speech phenomena such as harmonic...

Hilbert envelope based spectro-temporal features for phoneme recognition in telephone speech

In this paper, we present a spectro-temporal feature extraction technique using sub-band Hilbert envelopes of relatively long segments of speech signal. Hilbert envelopes of the sub-bands are estimated using Frequency Domain Linear Prediction (FDLP). Spectral features are derived by integrating the sub-band Hilbert envelopes in short-term frames and the temporal features are formed by convertin...

Hierarchical Spectro-Temporal Models for Speech Recognition

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...