Karthika Vijayan

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The objective of this paper is to establish the importance of phase of analytic signal of speech, referred to as the analytic phase, in human perception of speaker identity, as well as in automatic speaker verification. Subjective studies are conducted using analytic phase distorted speech signals, and the adversities occurred in human speaker verification(More)
The objective of this paper is to demonstrate the usefulness of phase derived from the linear prediction (LP) residual for speaker recognition. Though the sequence of samples in the LP residual are uncorrelated, they are not independent. Since the magnitude spectrum of the LP residual is almost flat, the dependencies among the samples in LP residual are(More)
Identification of epochs from speech signals is a prominent task in speech processing. In this paper, epoch extraction is attempted from phase spectrum of speech signals. The phase spectrum of speech is modelled as an allpass (AP) filter by minimizing entropy of energy in the associated error signal. The AP residual thus obtained contains prominent(More)
The phase spectrum of Fourier transform has received lesser prominence than its magnitude counterpart in speech processing. In this paper, we propose a method for parametric modeling of the phase spectrum, and discuss its applications in speech signal processing. The phase spectrum is modeled as the response of an allpass (AP) filter, whose coefficients are(More)
This paper proposes features based on parametric representation of Fourier phase of speech for speaker verification. Direct computation of Fourier phase suffers from phase wrapping and hence we attempt parametric modelling of phase spectrum using an allpass (AP) filter. The coefficients of the AP filter are estimated by minimizing an entropy based objective(More)
The objective of this work is to study the suitability of existing spectral mapping methods for enhancement of throat microphone (TM) speech, and propose a more elegant method for spectral mapping. Gaussian mixture models (GMM) and neural networks (NN) have been used for spectral mapping. Though GMM-based mapping captures the variability among speech sounds(More)
The significance of features derived from complex analytic domain representation of speech, for different applications, is investigated. Frequency domain linear prediction (FDLP) coefficients are derived from analytic magnitude and instantaneous frequency (IF) coefficients are derived from analytic phase of speech signals. Minimal pair ABX (MP-ABX) tasks(More)
This paper presents an epoch extraction method from the phase spectrum of speech signals. The phase spectrum of speech is modelled as the response of an allpass (AP) system. The coefficients of AP system are estimated by imposing sparsity constraint on the input signal. The AP residual is estimated using orthogonal matching pursuit and it is found that the(More)
Classification of organisms into different categories using their genomic sequences has found importance in study of evolutionary characteristics, specific identification of previously unknown organisms, study of mutual relationships between organisms and many other aspects in the study of living things. Chaos game representation (CGR) uniquely represents(More)