  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.
