Emotion is an intense feeling directed towards someone or something. One way that humans can express angry emotions that can be recognized is through speech. Speech emotion recognition is a technology that can be used to identify emotions from the sound of someone speaking. In this research, a speech emotion recognition process was carried out using the WFCC (Wavelet-based Frequency Cepstral Coefficients) method, which uses wavelet transformation in its extraction and has the ability to separate various frequency variations at various times. In addition, this study also tested the ability of the K-Nearest Neighbor algorithm in classifying the intensity of angry emotions from sound signals. This study was conducted using a Raspberry Pi 4. This study concluded that the WFCC extraction method is quite effective in detecting high intensity angry emotions with an accuracy of 66.67%.