REAL TIME SPEECH EMOTION RECOGNITION USING MACHINE LEARNING

Abstract

A speech recognition system, which can detect emotions contained in the dataset such as sad, happy, neural, angry, disgust, surprised, fearful and calm expressions. In real time we can use this application in various decisions. Although we are in a pandemic situation all processes are taking place only through online like job interviews, doctor appointments etc. In these cases this application is very useful whether in what state they are and to detect their emotions through speech. Here we are using a library called Librosa. Librosa is a python package for music and audio analysis. It provides the building blocks necessary to concoct music information retrieval systems. It was developed by Brian McFee, assistant professor of music technology and data science at NYU, and creator of Librosa, a python package for music and audio analysis. Librosa upholds a few elements connected with sound records handling and extraction like burden sound from a circle, register of different spectrogram portrayals, symphonious percussive source detachment, conventional spectrogram decay, stacks and translates the sound, Timespace sound handling, successive demonstrating, coordinating consonant percussive partition, beatsimultaneous and some more.