To derive spectro-temporal vocal source features complementary to the conventional spectral-based vocal tract features in improving the performance and reliability of a speaker recognition system, the excitation related modulation properties are studied. Through multi-band demodulation method, sourcerelated amplitude and phase quantities are parameterized into feature vectors. Evaluation of the...

Spectro-temporal modulations (STMs) of the sound convey timbre and rhythm information so that they are intuitively useful for automatic music genre classification. The STMs are usually extracted from a time-frequency representation of the acoustic signal. In this paper, we investigate the efficacy of two kinds of STM features, the Gabor features and the rate-scale (RS) features, selectively ext...

Title of Document: Representation of speech in the primary auditory cortex and its implications for robust speech processing. Nima Mesgarani, Ph.D., 2008 Directed By: Professor Shihab Shamma, Electrical and Computer Engineering Department Speech has evolved as a primary form of communication between humans. This most used means of communication has been the subject of intense study for years, b...

Across multiple timescales, acoustic regularities of speech match rhythmic properties of both the auditory and motor systems. Syllabic rate corresponds to natural jaw-associated oscillatory rhythms, and phonemic length could reflect endogenous oscillatory auditory cortical properties. Hemispheric lateralization for speech could result from an asymmetry of cortical tuning, with left and right au...

The organization of postthalamic auditory areas remains unclear in many respects. Using a stimulus based on properties of natural sounds, we mapped spectro-temporal receptive fields (STRFs) of neurons in the primary auditory area field L of unanesthetized zebra finches. Cells were sensitive to only a subset of possible acoustic features: nearly all neurons were narrowly tuned along the spectral...

Conventional speech recognition is notoriously vulnerable to additive noise, and even the best compensation methods are defeated if the noise is nonstationary. To address this problem, we propose a new integration of bottom-up techniques to identify ‘coherent fragments’ of spectro-temporal energy (based on local features), with the top-down hypothesis search of conventional speech recognition, ...

This paper describes a speaker verification system which uses two complementary acoustic features: Mel-frequency cepstral coefficients (MFCC) and wavelet octave coefficients of residues (WOCOR). While MFCC characterizes mainly the spectral envelope, or the formant structure of the vocal tract system, WOCOR aims at representing the spectro-temporal characteristics of the vocal source excitation....

In this paper, a new method is presented to extract robust speech features in the presence of the external noise. The proposed method based on two-dimensional Gabor filters takes in account the spectro-temporal modulation frequencies and also limits the redundancy on the feature level. The performance of the proposed feature extraction method was evaluated on isolated speech words which are ext...

This work analyzes the constant-Q filterbank-based time-frequency representations for speech emotion recognition (SER). Constant-Q filterbank provides non-linear spectro-temporal representation with higher frequency resolution at low frequencies. Our investigation reveals how increased low-frequency benefits SER. The time-domain comparative analysis between short-term mel-frequency spectral coe...

Parametric spectro-temporal analyzer (PASTA) is an entirely new wavelength resolving modality that focuses the spectral information on the temporal axis, enables ultrafast frame rate, and provides comparable resolution and sensitivity to the state-of-art optical spectrum analyzer (OSA). Generally, spectroscopy relies on the allocation of the spectrum onto the spatial or temporal domain, and the...