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Name - Rashmi Rani (21ENG7CSE0012)

Branch - Computer Science & Engineering

Faculty - Faculty of Engineering & Technology

Date of Registration - 4th July 2022

Supervisor - Dr. Manoj Kumar Ramaiya, Professor.

Date of Ph.D. Viva - 9th April 2026 (Thursday) at 11.00 AM

Title - Speech Emotion Detection System using Deep Learning Techniques


1. Rashmi Rani, Dr. Manoj Kumar Ramaiya, Dr. Abhay Kothari “A Brief Survey on Different Traditional and Deep Learning Techniques Used for Emotion Detection System from Speech Data”, Dogo Rangsang Research
Journal, ISSN: 2347-7180, UGC Care Group I Journal, Vol-13 Issue-04 No. 04 April 2023.

2. Rashmi Rani, Dr. Manoj Kumar Ramaiya “Speech Emotion Recognition using MFCC Features and LSTM Network” in Grenze International Journal of Engineering and Technology, January Issue, Grenze ID:
01.GIJET.11.1.334_1. © Grenze Scientific Society, 2025.

3. Rashmi Rani, Dr. Manoj Kumar Ramaiya “Detection of Emotions from Speech using Deep Learning Techniques and Traditional Techniques: A Survey”, Proceedings of the Second International Conference on Automation, Computing and Renewable Systems (ICACRS-2023), DVD Part Number: CFP23CB5-DVD; ISBN: 979-8-3503-4022-8, 979-8-3503-4023-5/23/$31.00 ©2023 IEEE.

4. Rashmi Rani, Dr. Manoj Kumar Ramaiya “Enhancing Speech Emotion Recognition with Multi-Modal Hybrid Features and CNN” SSRG International Journal of Electronics and Communication Engineering Volume
12 Issue 7, 35-46, July 2025, ISSN: 2348-8549/ https://doi.org/10.14445/23488549/IJECE-V12I7P104.

5. Rashmi Rani, Dr. Manoj Kumar Ramaiya “MEL Frequency Features Driven Deep Learning for Speech Emotion Detection: A Novel Model” published in 2025 International Conference on Computational,
Communication and Information Technology (ICCCIT) | 979-8-3315-1296-5/25/$31.00 ©2025 IEEE | DOI: 10.1109/ICCCIT62592.2025.10927747

6. Rashmi Rani, Dr. Manoj Kumar Ramaiya “Emotion Recognition on Speech using Hybrid Model CNN and BI-LSTM Techniques” published at researchsquare.com, October 2024, https://doi.org/10.21203/rs.3.rs-
5035263/v1, This work is licensed under a CC BY 4.0 License.