Voice Analysis for Stress Detection and Application in Virtual Reality to Improve Public Speaking in Real-time: A Review

TL;DR

This paper reviews the current state of voice-based stress detection during public speaking, highlighting gaps and proposing a real-time algorithm integrated with VR to help users manage stress and enhance speaking skills.

Contribution

It introduces a novel computational model for real-time voice-based stress detection that can be integrated into VR applications for public speaking training.

Findings

Identified key challenges in real-time stress detection during public speaking.

Proposed a new voice analysis algorithm for stress detection in VR environments.

Outlined potential improvements in public speaking training through stress management.

Abstract

Stress during public speaking is common and adversely affects performance and self-confidence. Extensive research has been carried out to develop various models to recognize emotional states. However, minimal research has been conducted to detect stress during public speaking in real time using voice analysis. In this context, the current review showed that the application of algorithms was not properly explored and helped identify the main obstacles in creating a suitable testing environment while accounting for current complexities and limitations. In this paper, we present our main idea and propose a stress detection computational algorithmic model that could be integrated into a Virtual Reality (VR) application to create an intelligent virtual audience for improving public speaking skills. The developed model, when integrated with VR, will be able to detect excessive stress in real time by analysing voice features correlated to physiological parameters indicative of stress and help users gradually control excessive stress and improve public speaking performance