A Study on Feature Values as a Speaker Identification Method

Automatic speaker assignment can enhance the efficiency of automated systems used for creating meeting minutes. Therefore, various methods of speaker identification have been widely utilized; however, in such methods, it is necessary to optimally arrange the equipment. In this paper, we propose a method for identifying speakers using an omnidirectional camera and a microphone. In this process, tens of minutes of image and voice data were used for model training, and the speaker was successfully identified. In the speaker discrimination experiments, the proposed method was able to identify the speaker with an average success rate of more than 70.0% using the lip height and product of the lip height feature and lip width feature as the lip movement features.