Speech segmentation using extrema based signal track length measure

We introduce a novel temporal feature of a signal, namely extrema-based signal track length (ESTL) for the problem of speech segmentation. We show that ESTL measure is sensitive to both amplitude and frequency of the signal. The short-time ESTL (ST_ESTL) shows a promising way to capture the significant segments of speech signal, where the segments correspond to acoustic units of speech having distinct temporal waveforms. We compare ESTL based segmentation with ML and STM methods and find that it is as good as spectral feature based segmentation, but with lesser computational complexity.

Extrema based unwarping for time-varying pitch estimation

We present an extrema based unwarping technique for signals with time-varying periodicity. We show that for arbitrary variation of pitch periodicity in speech signal,the unwarping technique maps the signals to periodic signals which enable eficient estimation of periodicity. We demonstrate the e�ectiveness of the new technique using both synthetic and real speech signals.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Spin-Probe ESR Studies on Nanocomposite Polymer Electrolytes

The possibility of using spin-probe electron spin resonance (ESR) as a tool to study glass transition temperature, T g, of polymer electrolytes is explored in 4 hydroxy 2,2,6,6 tetramethylpiperidine N oxyl (TEMPOL) doped composite polymer electrolyte (PEG)46LiClO4 dispersed with nanoparticles of hydrotalcite. The T g is estimated from the measured values of T 50G, the temperature at which the extrema separation 2A zz of the broad powder spectrum decreases to 50 G. In another method, the correlation time τc for the spin probe dynamics was determined by computer simulation of the ESR spectra and T g has been identified as the temperature at which τc begins to show temperature dependence. While both methods give values of T g close to those obtained from differential scanning calorimetry, it is concluded that more work is required to establish spin-probe ESR as a reliable technique for the determination of T g.

Conservation law with the flux function discontinuous in the space variable- II - Convex-concave type fluxes and generalized entropy solutions

We deal with a single conservation law with discontinuous convex-concave type fluxes which arise while considering sign changing flux coefficients. The main difficulty is that a weak solution may not exist as the Rankine-Hugoniot condition at the interface may not be satisfied for certain choice of the initial data. We develop the concept of generalized entropy solutions for such equations by replacing the Rankine-Hugoniot condition by a generalized Rankine-Hugoniot condition. The uniqueness of solutions is shown by proving that the generalized entropy solutions form a contractive semi-group in L-1. Existence follows by showing that a Godunov type finite difference scheme converges to the generalized entropy solution. The scheme is based on solutions of the associated Riemann problem and is neither consistent nor conservative. The analysis developed here enables to treat the cases of fluxes having at most one extrema in the domain of definition completely. Numerical results reporting the performance of the scheme are presented. (C) 2006 Elsevier B.V. All rights reserved.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Design of solid electrolytes for use with dissimilar gas electrodes

The design of a solid electrolyte that permits the use of dissimilar gas electrodes in an electrochemical cell is presented. It consists of a functionally gradient material with spatial variation in composition. The activity of the conducting ion is fixed at each electrode using different gas species. The system chosen for demonstrating the concept consists of a solid solution between K2CO3 and K2SO4. The composition of the solid solution varies from pure K2CO3 in contact with a CO2 + O2 gas mixture at one electrode to pure K2SO4 exposed to a mixture of SO3 + SO2 + O2 at the other. Two types of composition profiles are studied, one with monotonic variation in composition and the other with extrema. The e.m.f. of the cells is studied as a function of temperature and composition of the gas mixture at each electrode. The results indicate that the e.m.f. is determined primarily by the difference in the chemical potential of potassium at the two electrodes. The diffusion potential caused by ionic concentration gradients in the electrolyte appears to be negligible when the corresponding ionic transport numbers are insignificant. Studies on the response characteristics of the cell based on the gradient electrolyte indicate that the nature of the variation in composition of the electrolyte has only a minor effect on the time evolution of e.m.f. The gradient solid electrolytes have potential application in multielement galvanic sensors at high temperatures.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.