ABSTRACT
Emotion detection or sentiment analysis has been restricted mainly to linguistic analysis using text. Even if audio signals are considered it is used to identify words from the voice signal. The most obvious weakness of this method is exposed when machines are pitted against lying humans. This chapter aims to understand sentiments from the traditional models of emotion classification like the Plutchick model, PANA model, and others. Later, this chapter explores the programming tools and machine learning algorithms used to successfully detect emotions from speech. Finally, examples are provided at the end of the chapter regarding the uses of such a system.
