• T. Navya Deepthi
• Dr.A.Senthil Kumar
• Pasupuleti Sandhya
• Kondaveeti Aiswarya
• Bellamkonda Nandini , Shaik Mobeena Farhana

Presently, creative professions have been taken over by computers already.So, Artificial Intelligence fields are Machine Learning and Natural Language Processing, Computer Vision and Robotics had ended up part of it. Computers can also predict voice recognition the same way. Numerous files contain a range of audio and video recordings it also has information in big documents or records which might have numerous minutes to listen. We have come to appreciate this field overall and as part of our continued exposure during the paper deep dive series, today with be reviewing current trends in Deep learning for Speech Emotion Recognition. The purpose of this paper is to explore the most recent and significant works in deep learning methodologies for speech emotion recognition, their performance, and discuss what they have addressed till now. We also examine the existing literature, describe various CNNs and RNN models as well as hybrid approaches. Results reveal notable enhancements in emotion prediction with deep learning methods, highlighting the need for powerful feature vectors and model training. It also discussed the future direction as well as challenge in this field.

CNN, emotional speech database, DNN,MFCC, Spectrograms.

"SPEECH EMOTION RECOGNITION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.243-251, October-2024, Available :http://www.jetir.org/papers/JETIRGN06028.pdf

"SPEECH EMOTION RECOGNITION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp243-251, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06028.pdf