Detection and Analysis of Human Emotions through Voice and Speech Pattern Processing

TL;DR

This paper introduces an algorithmic method for detecting and analyzing human emotions through voice and speech attributes, aiming to enhance human-computer interaction systems with emotional awareness.

Contribution

It presents a novel approach for emotion detection from speech attributes, integrating voice analysis into AI systems for better interaction understanding.

Findings

Effective detection of emotions from speech attributes

Potential applications in human-computer interaction

Foundation for AI systems with emotional intelligence

Abstract

The ability to modulate vocal sounds and generate speech is one of the features which set humans apart from other living beings. The human voice can be characterized by several attributes such as pitch, timbre, loudness, and vocal tone. It has often been observed that humans express their emotions by varying different vocal attributes during speech generation. Hence, deduction of human emotions through voice and speech analysis has a practical plausibility and could potentially be beneficial for improving human conversational and persuasion skills. This paper presents an algorithmic approach for detection and analysis of human emotions with the help of voice and speech processing. The proposed approach has been developed with the objective of incorporation with futuristic artificial intelligence systems for improving human-computer interactions.