Conference Papers
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Item Identification of Voicing Assimilation From Children’s Speech(Institute of Electrical and Electronics Engineers Inc., 2017) Ramteke, P.B.; Madugula, M.; Suresh, S.; Koolagudi, S.G.In this paper, an attempt has been made for the automatic identification of the voicing assimilation or harmony process. In these processes the voiced sounds are replaced by unvoiced sounds and vice versa. The phonological processes appear in the children represent the age wise speech learning ability, where the processes start to disappear as children grow. Speech Language Pathologists (SLPs) analyse these processes to evaluate the learning ability of the children. The pitch is present in voiced speech and absent in unvoiced region of speech. This gives the clear view of the assimilation; hence pitch is explored for the identification of voicing assimilation. Features extracted from the test words (mispronounced words) are compared with the reference/correct words using Dynamic Time Warping (DTW) and region of mispronunciation is identified from the properties of DTW curve. The highest accuracy of identifying voicing assimilation achieved using pitch feature is 88%. © INDIACom-2017.Item Damage identification and assessment using image processing on post-disaster satellite imagery(Institute of Electrical and Electronics Engineers Inc., 2017) Joshi, A.R.; Tarte, I.; Suresh, S.; Koolagudi, S.G.Natural disasters such as earthquakes and tsunamis often have a devastating effect on human life and cause noticeable damage to infrastructure. Active research has been ongoing to mitigate the impact of these catastrophes and preclude the economic losses. The existing methods that utilize pre-event and post-event images not only require the immediate and guaranteed availability of the appropriate data set but are also encumbered by manual mapping of the images, necessitating the indication of corresponding control points in the two images. This paper highlights the use of only post-event imagery in the absence of reference data to achieve a more timely delivery to produce damage maps as the output. This eliminates the need for manual georeferencing of images. Our method incorporates simple linear iterative clustering (SLIC) for segmenting the images into uniform superpixels and extraction of 62 features for each superpixel. We used various classifiers of which Random Forest classifier was found to give a comparatively high accuracy of 90.4% over others. To enumerate the accuracy of the method proposed, we used 1500 data regions of which 20% were used for testing, and 80% were used for training. The aerial images taken by GeoEye1 after the 2011 Christchurch earthquake and 2011 Japan earthquake and tsunami are utilized in this study to detect building damage. In the case of availability of ground truth, we compare the histograms of the pre- and post-imagery to quantify similarity as the SSD (Sum of Squared Distances) value and thus, our approach produces an assessment as an output map displaying the extent of damage in the area covered by each superpixel. We consider 6 levels of damage ranging from 1 to 6, where 1 signifies no damage, and 6, maximum damage. © 2017 IEEE.Item A Framework for Quality Enhancement of Multispectral Remote Sensing Images(Institute of Electrical and Electronics Engineers Inc., 2018) Suresh, S.; Das, D.; Lal, S.Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images. © 2017 IEEE.Item Influence of Process Parameters on Microstructural Properties of L-DED Produced Ti64 Alloy(Springer Science and Business Media Deutschland GmbH, 2025) Suresh, S.; Kuriachen, B.; Kumar, V.; Bontha, S.; Gurugubelli, R.C.Additive manufacturing (AM) techniques have revolutionized the manufacturing of complex and customized parts across various applications. However, they are known for producing titanium parts with high anisotropy and low ductility, due to high cooling gradient in the build direction and the presence of martensite phase in microstructure respectively. These are inherent problems which limit their application in critical engineering fields. Laser—Direct Energy Deposition (L-DED) produced parts also have the same disadvantages. Thus, the primary objective of this paper is to identify the optimal combination of process parameters for L-DED that can mitigate these inherent limitations. Keeping the parameters such as powder size, orientation angle and hatch angle as constant, the laser power and scan speed are varied to fabricate 9 different sets of samples using L-DED. The research methodology includes an analysis of the microstructure, focusing on grain width, phase distribution, lath characteristics and presence of defects, if any. Microscopy and XRD techniques were used to observe the microstructure. Additionally, hardness studies were performed to evaluate the changes in material hardness. It was noticed that laser power significantly influences β width and α’ length while scan speed has a lesser dominant effect on both of them. The findings will contribute to the development of process-structure-property relations for L-DED-produced Ti64 and further, optimized manufacturing strategies for producing titanium parts with reduced anisotropy and increased ductility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.