Speaker and Context Independent Emotion Recognition using Speech Signal

음성을 이용한 화자 및 문장독립 감정인식

In this paper, speaker and context independent emotion recognition using speech signal is studied. For this purpose, a corpus of emotional speech data recorded and classified according to the emotion using the subjective evaluation were used to make statical feature vectors such as average, standard deviation and maximum value of pitch and energy and to evaluate the performance of the conventional pattern matching algorithms. The vector quantization based emotion recognition system is proposed for speaker and context independent emotion recognition. Experimental results showed that vector quantization based emotion recognizer using MFCC parameters showed better performance than that using the Pitch and energy Parameters.