Efficient post-processing techniques for speech enhancement

We address the problem of speech enhancement in real-world noisy scenarios. We propose to solve the problem in two stages, the first comprising a generalized spectral subtraction technique, followed by a sequence of perceptually-motivated post-processing algorithms. The role of the post-processing algorithms is to compensate for the effects of noise as well as to suppress any artifacts created by the first-stage processing. The key post-processing mechanisms are aimed at suppressing musical noise and to enhance the formant structure of voiced speech as well as to denoise the linear-prediction residual. The parameter values in the techniques are fixed optimally by experimentally evaluating the enhancement performance as a function of the parameters. We used the Carnegie-Mellon university Arctic database for our experiments. We considered three real-world noise types: fan noise, car noise, and motorbike noise. The enhancement performance was evaluated by conducting listening experiments on 12 subjects. The listeners reported a clear improvement (MOS improvement of 0.5 on an average) over the noisy signal in the perceived quality (increase in the mean-opinion score (MOS)) for positive signal-to-noise-ratios (SNRs). For negative SNRs, however, the improvement was found to be marginal.

A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

Evaluation of census techniques to estimate the density of slender Loris (Loris lydekkerianus) in Southern India

Reliable estimates of species density are fundamental to planning conservation strategies for any species; further, it is equally crucial to identify the most appropriate technique to estimate animal density. Nocturnal, small-sized animal species are notoriously difficult to census accurately and this issue critically affects their conservation status, We carried out a field study in southern India to estimate the density of slender loris, a small-sized nocturnal primate using line and strip transects. Actual counts of study individuals yielded a density estimate of 1.61 ha(-1); density estimate from line transects was 1.08 ha(-1); and density estimates varied from 1.06 ha(-1) to 0.59 ha(-1) in different fixed-width strip transects. We conclude that line and strip transects may typically underestimate densities of cryptic, nocturnal primates.

Some studies on evaluation of degradation in composite adhesive joints using ultrasonic techniques

Experimental and theoretical studies on degradation of composite-epoxy adhesive joints were carried out on samples having different interfacial and cohesive properties. Oblique incidence ultrasonic inspection of bonded joints revealed that degradation in the adhesive can be measured by significant variation in reflection amplitude as also by a shift in the minima of reflection spectrum. It was observed that severe degradation of the adhesive leads to failure dominated by interfacial mode. Through this investigation it is demonstrated that a correlation exists between the bond strength and a frequency shift in reflection minimum. The experimental data was validated using analytical models. Though both bulk adhesive degradation and interfacial degradation influences the shift in spectrum minimum, the contribution of the latter was found to be significant. An inversion algorithm was used to determine the interfacial transverse stiffness using the experimental oblique reflection spectrum. The spectrum shift was found to depend on the value of interfacial transverse stiffness using which a qualitative assessment can be made on the integrity of the joint.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Combining indentation and diffusion couple techniques for combinatorial discovery of high temperature shape memory alloys

We demonstrate the possibility of accelerated identification of potential compositions for high-temperature shape memory alloys (SMAs) through a combinatorial material synthesis and analysis approach, wherein we employ the combination of diffusion couple and indentation techniques. The former was utilized to generate smooth and compositionally graded inter-diffusion zones (IDZs) in the Ni-Ti-Pd ternary alloy system of varying IDZ thickness, depending on the annealing time at high temperature. The IDZs thus produced were then impressed with an indenter with a spherical tip so as to inscribe a predetermined indentation strain. Subsequent annealing of the indented samples at various elevated temperatures, T-a, ranging between 150 and 550 degrees C allows for partial to full relaxation of the strain imposed due to the shape memory effect. If T-a is above the austenite finish temperature, A(f), the relaxation will be complete. By measuring the depth recovery, which serves as a proxy for the shape recovery characteristic of the SMA, a three-dimensional map in the recovery temperature composition space is constructed. A comparison of the published Af data for different compositions with the Ta data shows good agreement when the depth recovery is between 70% and 80%, indicating that the methodology proposed in this paper can be utilized for the identification of promising compositions. Advantages and further possibilities of this methodology are discussed.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

COMPARISON AND CROSS-VALIDATION OF OPTICAL TECHNIQUES IN DIFFERENT SWIRL SPRAY REGIMES

This paper deals with an experimental study of pressure-swirl hydraulic injector nozzles using non-intrusive optical techniques. Experiments were conducted to study atomization characteristics using two nozzles with different orifice diameters, 0.3 mm and 0.5 mm, and injection pressures, 0.3-3.5 Mpa, which correspond to Reynolds number (Re-p) = 7,000-45,000, depending on nozzle utilized. Three laser diagnostic techniques were utilized: Shadowgraph, PIV (Particle Image Velocimetry), and PDPA (Phase Doppler Particle Anemometry). Measurements made in the spray in both axial and radial directions indicate that velocity, average droplet diameter profiles, and spray dynamics are highly dependent on the nozzle characteristics and injection pressure. Limitations of these techniques in the different flow regimes, related to the primary and secondary breakups as well as coalescence, are provided. Results indicate that all three techniques provide similar results throughout the different regimes. Shadowgraph and PDPA were possible in the secondary atomization and coalescence regimes while PIV measurements could be made only at the end of secondary atomization and coalescence.

Signal Detection in Generalized Gaussian Noise by Nonlinear Wavelet Denoising

In this paper, a nonlinear suboptimal detector whose performance in heavy-tailed noise is significantly better than that of the matched filter is proposed. The detector consists of a nonlinear wavelet denoising filter to enhance the signal-to-noise ratio, followed by a replica correlator. Performance of the detector is investigated through an asymptotic theoretical analysis as well as Monte Carlo simulations. The proposed detector offers the following advantages over the optimal (in the Neyman-Pearson sense) detector: it is easier to implement, and it is more robust with respect to error in modeling the probability distribution of noise.

Flexibility in Food Extraction Techniques in Urban Free-Ranging Bonnet Macaques, Macaca radiata

Non-human primate populations, other than responding appropriately to naturally occurring challenges, also need to cope with anthropogenic factors such as environmental pollution, resource depletion, and habitat destruction. Populations and individuals are likely to show considerable variations in food extraction abilities, with some populations and individuals more efficient than others at exploiting a set of resources. In this study, we examined among urban free-ranging bonnet macaques, Macaca radiata (a) local differences in food extraction abilities, (b) between-individual variation and within-individual consistency in problem-solving success and the underlying problem-solving characteristics, and (c) behavioral patterns associated with higher efficiency in food extraction. When presented with novel food extraction tasks, the urban macaques having more frequent exposure to novel physical objects in their surroundings, extracted food material from PET bottles and also solved another food extraction task (i.e., extracting an orange from a wire mesh box), more often than those living under more natural conditions. Adults solved the tasks more frequently than juveniles, and females more frequently than males. Both solution-technique and problem-solving characteristics varied across individuals but remained consistent within each individual across the successive presentations of PET bottles. The macaques that solved the tasks showed lesser within-individual variation in their food extraction behavior as compared to those that failed to solve the tasks. A few macaques appropriately modified their problem-solving behavior in accordance with the task requirements and solved the modified versions of the tasks without trial-and-error learning. These observations are ecologically relevant - they demonstrate considerable local differences in food extraction abilities, between-individual variation and within-individual consistency in food extraction techniques among free-ranging bonnet macaques, possibly affecting the species' local adaptability and resilience to environmental changes.

Study on the Effect of Dead Time and its Compensation for Bus-Clamping PWM Techniques

Dead-time is provided in between the gating signals of the top and bottom semiconductor switches in an inverter leg to prevent the shorting of DC bus. Due to this dead time, there is a significant unwanted change in the output voltage of the inverter. The effect is different for different pulse width modulation (PWM) methodologies. The effect of dead-time on the output fundamental voltage is studied theoretically as well as experimentally for bus-clamping PWM methodologies. Further, experimental observations on the effectiveness of dead-time compensation are presented.

A Quick-Simulation Tool for Induction Motor Drives Controlled Using Advanced Space-Vector-Based PWM Techniques

Space-vector-based pulse width modulation (PWM) for a voltage source inverter (VSI) offers flexibility in terms of different switching sequences. Numerical simulation is helpful to assess the performance of a PWM method before actual implementation. A quick-simulation tool to simulate a variety of space-vector-based PWM strategies for a two-level VSI-fed squirrel cage induction motor drive is presented. The simulator is developed using C and Python programming languages, and has a graphical user interface (GUI) also. The prime focus being PWM strategies, the simulator developed is 40 times faster than MATLAB in terms of the actual time taken for a simulation. Simulation and experimental results are presented on a 5-hp ac motor drive.

Acoustic emission techniques for NDE & structural health monitoring of advanced composite materials

Structural Health Monitoring (SHM) is an effective extension of NDE to reduce down time and cost of Inspection of structural components. On – line monitoring is an essential part of SHM. Acoustic Emission Techniques have most of the desirable requirements of an effective SHM tool. With the kind of advancement seen in the last couple of decades in the field of electronics, computers and signal processing technologies it can only be more helpful in obtaining better and meaningful quantitative results which can further enhance the potential of AET for the purpose. Advanced Composite materials owing to their specific high performance characteristics are finding a wide range of engineering applications. Testing and Evaluation of this category of materials and SHM of composite structures have been very challenging problems due to the very nature of these materials. Mechanical behaviour of fiber composite materials under different loading conditions is complex and involves different types of failure mechanisms. This is where the potential of AET can be exploited effectively. This paper presents an over view of some relevant studies where AET has been utilised to test, evaluate and monitor health of composite structures.

Analysis of the modulation process in advanced bus-clamping PWM techniques

Advanced bus-clamping pulse width modulation (ABCPWM) techniques are advantageous in terms of line current distortion and inverter switching loss in voltage source inverter-fed applications. However, the PWM waveforms corresponding to these techniques are not amenable to carrier-based generation. The modulation process in ABCPWM methods is analyzed here from a “per-phase” perspective. It is shown that three sets of descendant modulating functions (or modified modulating functions) can be generated from the three-phase sinusoidal signals. Each set of the modified modulating functions can be used to produce the PWM waveform of a given phase in a computationally efficient manner. Theoretical results and experimental investigations on a 5hp motor drive are presented