Comparing ANN and GMM in a voice conversion framework

In this paper, we present a comparative analysis of artificial neural networks (ANNs) and Gaussian mixture models (GMMs) for design of voice conversion system using line spectral frequencies (LSFs) as feature vectors. Both the ANN and GMM based models are explored to capture nonlinear mapping functions for modifying the vocal tract characteristics of a source speaker according to a desired target speaker. The LSFs are used to represent the vocal tract transfer function of a particular speaker. Mapping of the intonation patterns (pitch contour) is carried out using a codebook based model at segmental level. The energy profile of the signal is modified using a fixed scaling factor defined between the source and target speakers at the segmental level. Two different methods for residual modification such as residual copying and residual selection methods are used to generate the target residual signal. The performance of ANN and GMM based voice conversion (VC) system are conducted using subjective and objective measures. The results indicate that the proposed ANN-based model using LSFs feature set may be used as an alternative to state-of-the-art GMM-based models used to design a voice conversion system.     

Acidolysis Reaction of Sal Fat (Shorea robusta) with Palmitic Acid

Acidolysis reaction of sal fat (Shorea robusta) with palmitic acid has been studied in relation to the operating variables like catalyst system and concentration, reaction temperature and time and molar ratios of reactants with the object of introducing more palmitic acid which is low in sal fat. The results demonstrate that as low as 2.5% and as high as 39% palmitic acid can be introduced in sal fat at the expense of other acids under the influence of various operating conditions. The products obtained differ from original sal fat in respect of chemical composition and slip point. The importance of such study is that there are possibilities of getting plastic fats of diverse properties for edible and industrial uses.     

FracMAP: A user-interactive package for performing simulation and orientation-specific morphology analysis of fractal-like solid nano-agglomerates

Computer simulation techniques have found extensive use in establishing empirical relationships between three-dimensional (3d) and two-dimensional (2d) projected properties of particles produced by the process of growth through the agglomeration of smaller particles (monomers). In this paper, we describe a package, FracMAP, that has been written to simulate 3d quasi-fractal agglomerates and create their 2d pixelated projection images by restricting them to stable orientations as commonly encountered for quasi-fractal agglomerates collected on filter media for electron microscopy. Resulting 2d images are analyzed for their projected morphological properties.

Program summary

Program title: FracMAPCatalogue identifier: AEDD_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDD_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 4722No. of bytes in distributed program, including test data, etc.: 27 229Distribution format: tar.gzProgramming language: C++Computer: PCOperating system: Windows, LinuxRAM: 2.0 MegabytesClassification: 7.7Nature of problem: Solving for a suitable fractal agglomerate construction under constraints of typical morphological parameters.Solution method: Monte Carlo approximation.Restrictions: Problem complexity is not representative of run-time, since Monte Carlo iterations are of a constant complexity.Additional comments: The distribution file contains two versions of the FracMAP code, one for Windows and one for Linux.Running time: 1 hour for a fractal agglomerate of size 25 on a single processor.     

Dynamic Grover search: applications in recommendation systems and optimization problems

In the recent years, we have seen that Grover search algorithm (Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212–219, 1996) by using quantum parallelism has revolutionized the field of solving huge class of NP problems in comparisons to classical systems. In this work, we explore the idea of extending Grover search algorithm to approximate algorithms. Here we try to analyze the applicability of Grover search to process an unstructured database with a dynamic selection function in contrast to the static selection function used in the original work (Grover in Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212–219, 1996). We show that this alteration facilitates us to extend the application of Grover search to the field of randomized search algorithms. Further, we use the dynamic Grover search algorithm to define the goals for a recommendation system based on which we propose a recommendation algorithm which uses binomial similarity distribution space giving us a quadratic speedup over traditional classical unstructured recommendation systems. Finally, we see how dynamic Grover search can be used to tackle a wide range of optimization problems where we improve complexity over existing optimization algorithms.     

Electrical properties of vanadium pentoxide doped with lithium and sodium in the α-phase range

The electrical conductivity and Seebeck coefficients have been measured from room temperature to 500° C for polycrystalline V₂O₅ and V₂O₅ doped with lithium and sodium in the -phase range. The conductivity increases with doping and the energy of activation decreases. The Seebeck coefficient indicates that electrons are the majority carriers. The results have been discussed in terms of the two-level hopping model.     

Investigation of polyelectrolyte for electrochemical detection of uric acid in presence of ascorbic acid

Uric acid (UA) was detected in the presence of ascorbic acid (AA) at GC electrode by cyclic voltametry (CV) and differential pulse voltametry (DPV) in aqueous media of cationic polyelectrolyte (poly(diallyldimethylammonium chloride) (PDDA)). Both, UA and AA are anionic nature and electro-static attraction with cationic solution. This lowered their oxidation potentials and increased anodic current. In CV studies, the UA oxidation potential was decreased by 400 mV in the presence of PDDA along with increase in peak current. Effect of PDDA and pH on E_pa and I_pa were also studied. About 360 mV difference in oxidation peak potentials was observed for AA and UA in PDDA media, which established a quick method for their simultaneous determination. The detection limit of UA in the presence of 200 folds AA was found as 1 μM with correlation coefficient of 0.994 and sensitivity of 0.05 μA μM⁻¹. The proposed method has been also applied for determining the UA in human urine without any pretreatment, and found to be satisfactory.     

Direct Experimental Observations on Concurrent Microstructure and Magnetic Property Developments in Non-Grain Oriented Electrical Steel

Non-grain oriented electrical steel, with minor in-grain orientation gradients, was subjected to interrupted tensile deformations and concurrent microtexture, magnetic property and residual stress measurements. After the upper yield point, clear signatures of mechanical stress relief were observed. Changes in orientation gradients led to annihilation of low-angle (1 to 3 deg) boundaries. Prior deformation compressive residual stresses became tensile and magnetic properties improved. Beyond an optimum true strain of 0.01, this boundary annihilation ceased, compressive stresses were generated, and magnetic properties degraded.     

Fractality of tics as a quantitative assessment tool for Tourette syndrome

Tics manifest as brief, purposeless and unintentional movements or noises that, for many individuals, can be suppressed temporarily with effort. Previous work has hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbour-to-neighbour correlation at all levels of timescale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent—called the fractal dimension D_f—from fractional Brownian noise. Here, we confirm this hypothesis and establish the fractality of tics by examining two tic time series datasets collected 6–12 months apart in children with tics, using random walk models and directional statistics. We find that D_f is correlated with tic severity as measured by the YGTTS total tic score, and that D_f is a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. Our findings pave the way for using the fractal nature of tics as a robust quantitative tool for estimating tic severity and treatment effectiveness, as well as a possible marker for differentiating typical from functional tics.     

Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources

The identification of unknown pollution sources is a prerequisite for designing of a remediation strategy. In most of the real world situations, it is difficult to identify the pollution sources without a scientifically designed efficient monitoring network. The locations of the contaminant concentration measurement sites would determine the efficiency of the unknown source identification process to a large extent. Therefore coupled and iterative sequential source identification and dynamic monitoring network design framework is developed. The coupled approach provides a framework for necessary sequential exchange of information between monitoring network and source identification methodology. The preliminary identification of unknown sources, based on limited concentration data from existing arbitrarily located wells provides the initial rough estimate of the source fluxes. These identified source fluxes are then utilized for designing an optimal monitoring network for the first stage. Both the monitoring network and source identification process is repeated by sequential identification of sources and design of monitoring network which provides the feedback information. In the optimal source identification model, the Jacobian matrix which is the determinant for the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. For the optimal monitoring network design, the integer programming based optimal design model requires as input, simulated sets of concentration data. In the proposed methodology, the concentration measurement data from the designed and implemented monitoring network are used as feedback information for sequential identification of unknown pollution sources. The potential applicability of the developed methodology is demonstrated for an illustrative study area.     

2002 Annual Index

Authors Index

2002 Annual Index