IDENTIFICATION OF EMOTIONS FROM SPEECH

A fascinating and difficult task in human-computer interaction is recognizing emotions from speech. This topic has received a lot of interest recently. In the field of speech emotion recognition, many methods have been used to extract emotions from signals. This includes many well-known speech analysis and classification methods. Traditional methods of recognizing speech emotion extract features from the audio signal and select those features. This is a process known as the selection engine, which then identifies emotions. This is a very drawn-out process. Understand the importance of language, emotions and how they are important for emotion recognition. Identification of Emotions from our project has undergone extensive research for further research and development in the future. Automatically building speech recognition has proven effective in development. This project extends the research and development of emotion recognition through language using convolutional neural networks (CNNs). This project sheds light on using a CNN from a live video stream as input. Using various machine learning libraries such as Tensor Flow. Various fields have benefited from this development, such as medical technology, technology, and marketing.