AN EXECUTABLE METHOD FOR AN INTELLIGENT SPEECH AND CALL RECOGNITION SYSTEM USING A MACHINE LEARNING-BASED APPROACH

This paper describes a novel call recognizer system based on the machine learning approach. Current trends, intelligence, emotional recognition and other factors are important challenges in real world. The proposed provides robustness with high accuracy adequate response time for human–computer interaction. Intelligence emotion from speech of interfaces simulated via multiple classifier systems (MCSs). At higher-level stage, acoustic stream phase extracts certain features pitch energy signal. Here, feature space is labeled various types training phase. Emotional categories trained space. semantic process converts into text input Text classification algorithms applied subsequently. clustering performed [Formula: see text]-means algorithm. detection Tone Voice achieved XGBoost model extraction particular phrase client Speech expressions used understanding human emotion. tested demonstrate good performance simulation environment.