In the study, the effectiveness of combinations of cepstral features, channel compensation techniques, and different local distances in the Dynamic Time Warping (DTW) algorithm is experimentally evaluated in the text-dependent speaker identification task. The training and the testing has been done with noisy telephone speech (short phrases in Bulgarian with length of about 2 seconds) selected f...

In this article a new flexible speech detection method comprising two relatively modern approaches like artificial neural networks (ANN) and cepstral matrices is presented. Cepstral matrices obtained via linear prediction coefficients were chosen as the eligible speech features. This technique is known to provide reliable log spectrum estimation at a low cost. Furthermore, both spectral and tim...

The aim of this study was to assess the applicability of Mel Frequency Cepstral Coefficients (MFCC) of voice samples in diagnosing vocal nodules and polyps. Patients’ voice samples were analysed acoustically with the measurement of MFCC and values of the first three formants. Classification of mel coefficients was performed by applying the Sammon Mapping and Support Vector Machines. For the tes...

In this paper, we study the well-posedness of the problems of determining shaping filters from combinations of finite windows of cepstral coefficients, covariance lags, or Markov parameters. For example, we determine whether there exists a shaping filter with prescribed window of Markov parameters and a prescribed window of covariance lags. We show that several such problems are well-posed in t...

The article presents two methods of determination of cepstral parameters commonly applied in digital signal processing, in particular in speech recognition systems. The solutions presented are part of a project aimed at developing applications allowing to control the Windows operating system with voice and the use of MSAA (Microsoft Active Accessibility). The analysed voice signal has been visu...

NEURO BASED APPROACH FOR SPEECH RECOGNITION BY USING MEL-FREQUENCY CEPSTRAL COEFFICIENTS R.L.K. Venkateswarlu1 and R. Vasanthakumari2 1 Department of Information Technology, Sasi Institute of Technology and Engineering, Tadepalligudem, India, E-mail: [email protected]. 2 Perunthalaivar Kamarajar Arts College, Puducherry-605107, India, E-mail: [email protected]. This paper presents continu...

This paper presents an effort to provide a more efficient speech signal representation, which aims to be incorporated into an automatic speech recognition system. Modified cepstral coefficients, derived from a multiresolution auditory spectrum are proposed. The multiresolution spectrum was obtained using sliding single point discrete Fourier transformations. It is shown that the obtained spectr...

This study deals with the relation between the spectral representation and the perceptual identification of the Spanish fricatives and affricates. Several spectral representations have been analyzed: FFT-derived linear cepstrum, mel cepstrum coefficients, LPC cepstral coefficients and the first four statistical moments. Quadratic discriminant analysis including the leaveone-out method have been...

This paper exploits the nonlinear mapping property of feedforward neural networks for estimation of high frequency components (4-8kHz) of the speech signals from the band-limited (04kHz) signals. Cepstral coefficients are used to represent the feature vectors of each frame of data. This paper also proposes an approach that uses the autocorrelation method to derive the Linear Prediction (LP) coe...

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 function motivated from speech produc...