Rupali Virendrasingh Pawar
@keystoneschoolofengineering.com
Professor, E&TC Department
Shalaka Foundations Keystone School of Engineering
Rupali holds a Doctorate in E&TC engineering and has almost two decades of experience in academia and a year plus in the industry. She has taught several courses to PG-level university students and working professionals and to the UG students as well. Specifically, she has taught subjects such as Embedded Systems, Bio-Medical Engineering, Machine Learning, Deep Learning, and Data Science. In addition, she has assisted students in completing PG and UGlevel Projects and moderated on topics related to the domain of expertise.
Currently, she is associated with an Engineering College in Pune and is conducting lectures and practical on Machine Learning and Deep Learning Subjects using the open-source platform Python. She has presented several papers at national and international conferences and published articles in reputed journals in Speech Processing Domain.
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering
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Scopus Publications
Rupali V. Pawar, Rajesh M. Jalnekar, and Janardan S. Chitode
Springer Science and Business Media LLC
Rupali V. Pawar, R. M. Jalnekar, and J. S. Chitode
Springer Singapore
Rupali Pawar, R. M. Jalnekar, and J. S. Chitode
NADIA
Speaker recognition is an important application of Speech Signal Processing and has been used in public safety, authenticating users for important financial transactions, access control systems and many more. The conventional approach in speaker identification and speaker verification has been to remove the silence from the recorded speech signal and further extract the significant features from the residual signal for recognition. This paper presents an alternative approach and puts forth the experimental results of obtaining silence as a parameter to check if the pattern of pauses/silence for train and test files recorded for individual speaker match. The paper emphasizes the approach in which a paragraph is recorded for 8 speakers and used as train files. The duration of silence/pauses of the speaker in a paragraph are obtained. This silence obtained is compared with the silence obtained from test file the matching of pattern of the silences decides the identity of the speaker.
Aarti V. Jadhav and Rupali V. Pawar
IEEE
Speech recognition is an important application that enables interaction of human beings with machines. The various stages in speech recognition system are pre-emphasis, feature extraction and recognition stage. This paper emphasizes on existing techniques in each of these stages of speech recognition system and elaborates on their comparison.
D.B. Satre and R.V. Pawar
IEEE
In this paper, we have explained an algorithm for preserving robustness for image data hiding. Robust data hiding is the process of extraction the correct data after compression or any other alteration applied on the embedded image. Embedded image is the image that obtains after hiding some information on the original image. Our technique compare with the existing technique called Y. Q. Shi method. We are comparing results of both techniques, i.e., PSNR of the embedded image and the number of error bits introduced in the extracted data from the embedded image. Both the algorithm is implemented on all kind of images including aerial, texture, and miscellaneous image. It also successfully implemented on the medical image.
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INDUSTRY EXPERIENCE
Worked as Sr. R&D Engineer at Indpro Electronics Pvt Ltd, Pune for 1&1/2 years