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  9. Dr. Spoorthy Venkatesh

Dr. Spoorthy Venkatesh

Designation: Assistant Professor

Biography:

Dr. Spoorthy V. is an Assistant Professor at Adani University, Ahmedabad, specializing in machine learning and deep learning for auditory scene analysis and natural language processing. Her research advances human-centric acoustic modeling, focusing on sound event detection, source localization, and acoustic scene classification. She has published in reputed international conferences and journals, and serves as a peer reviewer for leading journals and conferences in the AI and speech domains. She also mentors undergraduate and postgraduate researchers, contributing to the development of intelligent, data-driven systems for real-world audio understanding and spoken communication technologies.

  • 2018–2024 – Ph.D. National Institute of Technology Karnataka Surathkal, (Computer Science and Engineering, CGPA: 9.33)
  • 2016–2018: M.Tech. National Institute of Technology Goa. (Computer Science and Engineering, CGPA: 8.46)
  • 2009–2013 – B.E. G M Institute of Technology, Visveswaraya Technological University. (Information Science and Engineering, Percentage: 70.1%)
  • HSC- March 2012, JSS College for Women, Mysore, Karnataka
  • SSC March 2010, Don Bosco ICSE School, Chitradurga, Karnataka

  • 2024 – July 2025 – Assistant Professor, Dept. of AI-ML, CSPIT, CHARUSAT

  • Audio processing
  • Speech Processing
  • Deep Learning
  • Machine Learning

  1. Venkatesh, Spoorthy, Manjunath Mulimani, and Shashidhar G. Koolagudi. “Acoustic Scene Classification using Deep Fisher network.” Digital Signal Processing (ELsevier), 139 (2023): 104062.
  2. Venkatesh, Spoorthy, and Shashidhar G. Koolagudi. “Bi-level Acoustic Scene Classification using Lightweight Deep Learning Model.” Circuits, Systems and Signal Processing (Springer) (2023): pp: 1-20
  3. Venkatesh, Spoorthy, and Shashidhar G. Koolagudi. “Polyphonic Sound Event Detection using Mel-Pseudo Constant Q-Transform and Deep Neural Network”, IETE Journal of Research (Taylor & Francis) (2023): pp: 1-13
  4. Venkatesh, Spoorthy, and Shashidhar G. Koolagudi. “Polyphonic Sound Event Localization and Detection using Channel-Wise FusionNet.” Applied Intelligence (Springer): (2024) pp:1-12
  5. Mulimani, M., Venkatesh, Spoorthy. & Koolagudi, S.G. “Acoustic Event and Scene Classification: A Review”. SN Computer Science (Springer). 6, 54 (2025)
  6. Kumar TG, Keerthan., Mendke Saish., Parihar, Rohit., Mayya, Samarth, Venkatesh, Spoorthy. & Koolagudi, S.G. “DBNLP: detecting bias in natural language processing system for India-centric languages”. International Journal of Information Technology (Springer): (2025) pp: 1-16

  1. Venkatesh, S., Koshti, N., Shringi, D. K., & Popat, M. Fake Video Detection Using Deep Learning-Based Methods. International Conference on Innovative Computing and Communication (ICICC), pp. 85–93, 2025.
  2. Venkatesh, S., Dodia, S., & Bhatt, N. A Research on Big Data Analytics using Artificial Intelligence. 8th International Conference on Information and Communication Technology for Intelligent Systems (ICTIS), Springer LNNS, vol. 1112, 2024.
  3. Savaliya, Z., Satasiya, L., Venkatesh, S., & Bhatt, N. Translating into Indian Language: The Effect of Artificial Intelligence. International Conference on Information and Communication Technology for Competitive Strategies (ICTCS), pp. 185–195, Springer Nature, 2024.
  4. Desai, K., Bambhroliya, O., Mistry, J., Venkatesh, S., & Bhatt, N. Voice Recognition Technology: Capabilities, Challenges, and Innovations. International Conference on Information and Communication Technology for Competitive Strategies (ICTCS), pp. 197–208, Springer Nature, 2024.
  5. Bhanushali, J., Goswami, N., Bhatt, N., & Venkatesh, S. Personality Prediction Using Myers-Briggs Type Indicator and Machine Learning Approaches. Congress on Intelligent Systems (CIS), pp. 473–484, Springer Nature, 2024.
  6. Venkatesh, S., & Koolagudi, S. G. Polyphonic Sound Event Detection using Modified Recurrent Temporal Pyramid Neural Network. 8th International Conference on Computer Vision and Image Processing (CVIP), 2023.
  7. Venkatesh, S., & Koolagudi, S. G. A Transpose-SELDNet for Polyphonic Sound Event Localization and Detection. IEEE 8th International Conference for Convergence in Technology (I2CT), pp. 1–6, 2023.
  8. Kishor, K., Venkatesh, S., & Koolagudi, S. G. Audio Fingerprinting System to Detect and Match Audio Recordings. 10th International Conference on Pattern Recognition and Machine Intelligence (PReMI), 2023.
  9. Dodia, S., Venkatesh, S., & Trupti, C. Machine Learning-based Automated System for Subjective Answer Evaluation. 9th International Conference on Electronics, Computing and Communication Technologies (CONECCT), pp. 1–6, 2023.
  10. Sinha, S., Venkatesh, S., & Koolagudi, S. G. Code-switching Automatic Speech Recognition using Modified ESPNet. AIP Conference Proceedings, 2745(1), 2023.
  11. Gupta, S. P., Venkatesh, S., & Koolagudi, S. G. Noise Cancellation by Fast Fourier Transform for Wav2Vec2.0 Based Speech-to-Text System. IEEE 8th International Conference for Convergence in Technology (I2CT), pp. 1–4, 2023.
  12. Venkatesh, S., & Koolagudi, S. G. Device Robust Acoustic Scene Classification using Adaptive Noise Reduction and Convolutional Recurrent Attention Neural Network. 24th International Conference on Speech and Computer (SPECOM), pp. 688–699, Springer, 2022.
  13. Antony, A., Kota, S. R., Lade, A., Venkatesh, S., & Koolagudi, S. G. An Improved Transformer Transducer Architecture for Hindi-English Code-Switched Speech Recognition. 23rd INTERSPEECH, pp. 3123–3127, 2022.
  14. Gupta, S. P., Venkatesh, S., & Koolagudi, S. G. Recognition of Fricative Phoneme Based Hindi Words in Speech-to-Text System Using Wav2Vec2.0 Model. IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT), vol. 5, pp. 1–5, 2022.
  15. Venkatesh, S., Mulimani, M., & Koolagudi, S. G. Acoustic Scene Classification using Deep Learning Architectures. IEEE 6th International Conference for Convergence in Technology (I2CT), pp. 1–6, 2021.
  16. Thomas, T., Venkatesh, S., Sobhana, N. V., & Koolagudi, S. G. Speaker Recognition in Emotional Environment using Excitation Features. 3rd International Conference on Advances in Electronics, Computers and Communications (ICAECC), pp. 1–6, 2020.
  17. Sandhya, P., Venkatesh, S., Koolagudi, S. G., & Sobhana, N. V. Spectral Features for Emotional Speaker Recognition. 3rd International Conference on Advances in Electronics, Computers and Communications (ICAECC), pp. 1-6, 2020.

  1. Title: System and Method for Identifying a Speaker’s Native Language from Second or Third Language Speech
  2. Application No.: 202541070075, Filed on 23 July 2025
  3. Inventors: Spoorthy Venkatesh, Shashidhar G. Koolagudi, Sourav Kanti Addya, Shreyansh Shrivastava, Tushar Dubey, Souhard Kataria
  4. Applicant: National Institute of Technology Karnataka

  • Best Paper Award for the Paper titled “Code-Switching Automatic Speech Recognition using Modified ESPNet” in the International Conference on Applied Mechanics, Machine Learning and Advanced Computation (AMMLAC-2022)

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