• Ms. Sheetal Rajwade
• Mrs. G. Mani

In the realm of human-machine interface applications, the investigation into emotion recognition from speech signals has been a longstanding research focus. Emotions hold a crucial role in human mental life, serving as a medium for expressing one's perspective or mental state to others. Speech Emotion Recognition (SER) involves extracting the emotional state of a speaker from their speech signal. Among the universal emotions are Neutral, Anger, Happiness, Sadness, Fear, etc., which can be identified or synthesized by intelligent systems with finite computational resources.This study focuses on extracting speech features, including Mel-frequency cepstral coefficients (MFCC), Chromogram, Mel-scaled spectrogram, along with Spectral contrast and Tonal Centroid features. Deep Neural Network (DNN) is employed for the classification of emotions in this work.

Human-Machine Interface,Emotional State,Speech Emotion Recognition,Neutral,Happiness,Anger,Sadness

"Emotion Recognition Using Speech Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.e275-e279, February-2024, Available :http://www.jetir.org/papers/JETIR2402437.pdf

"Emotion Recognition Using Speech Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppe275-e279, February-2024, Available at : http://www.jetir.org/papers/JETIR2402437.pdf