• AKSHAY MOHAN
• HRIDYA SB
• PRANAV BS
• SUBAHANA N
• JITHIN JACOB.

ven though creating effective classifiers has mostly relied on models that incorporate audio data, speech emotion recognition may be difficult. In the human lifespan, emotions play a significant part in communication, and in the modern digital world of remote communication, the detection and analysis of an equivalent are crucial. Since emotions are subjective, detecting them may be difficult. Concerning how to gauge or classify them, there is no widespread agreement. A speech emotion recognition system is described as a collection of techniques that classify and process speech signals to identify any emotions that may be present. By examining the acoustic char- acteristics of the audio data of recorded speech, we determined in this study to identify underlying emotions in Emotion is a natural and hereditary component of human conduct. The overall method of communication. Humans are educated to recognize a wide range of emotions via experience, which helps us to be more logical and perceptive. However, in the case of a machine, it can readily comprehend content-based information such as that presented in text, audio, or video but is still unable to grasp the depth of the content. Three types of features make up a speech: lexical features (the vocabulary used), visual features (the speaker’s facial expressions), and acoustic features (sound properties like pitch, tone, and jittered.)

Capsule Nets

"RECOGNITION OF HUMAN EMOTIONS FROM VOICE SAMPLES BY ML TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.i60-i62, March-2023, Available :http://www.jetir.org/papers/JETIR2303810.pdf

"RECOGNITION OF HUMAN EMOTIONS FROM VOICE SAMPLES BY ML TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppi60-i62, March-2023, Available at : http://www.jetir.org/papers/JETIR2303810.pdf