Emotional state analysis based on speech recognition signals

At present, as intelligent speech recognition is widely used, the importance of speech emotion recognition technology is also gradually gaining recognition. Considering the current social pressure, the generation of negative emotions has become particularly common. Therefore, it is necessary to increase the recognition of different emotions by using the speech recognition system, which has been perfected, so as to play a role in anticipation and prevention. In this paper, we focus on the negative effects of negative emotions on people's lives, and use K-nearest classifier to identify different emotions, and accurately identify them, and prevent and monitor them. Finally, the feasibility of this method is confirmed by simulating the process.