Development of a Real-time Embedded System for Speech Emotion Recognition

Abstract

Development of a Real-time Embedded System for Speech Emotion Recognition.Speech emotion recognition is one of the latest challenges in speech processing and Human Computer Interaction to address operational needs in real-world applications.Development of a Real-time Besides human facial expressions, projects reports on Development of a Real-time speech has proven to be one of the most promising modalities for automatic recognition of human emotions.

Speech is a spontaneous medium of perceived emotions which provides a thorough understanding of the different cognitive conditions of a human being.projects reports on Development of a Real-time In this context, we introduce a novel approach using a combination ofprosody features (i.e. pitch, energy, Zero crossing rate), quality features (i.e. FormantFrequencies, Spectral features etc. derived features Mel-Frequency Cepstral Coefficient(MFCC), Linear Predictive Coding Coefficients and dynamic feature (Mel-Energyspectrum dynamic Coefficients for robust automatic recognition of speaker’semotional states.

Introduction

 Development of a Real-time Projects on Development of a Real-time Machine learning that concerns the development of algorithms, enabling machine to learn through inductive inference based on observation data representing incomplete statistical phenomenon information.

Classification, also referred to as pattern recognition, is an important task in machine learning by which machines “learn” to automatically recognize complex patterns,projects on Development of a Real-time to distinguish between examples based on their different patterns, and to make intelligent decisions.

Conclusion

An implementable and robust real-time model for these applications may be a scope for future work.