Preprocessing Signal for Speech Emotion Recognition


In this paper the preprocessing signal for speech emotion recognition was introduced. The literature review on speech emotion recognition was presented. The discrimination between speech and music files was performed depend on a comparative between more than one statistical indicator such as mean, standard deviation, energy and silence interval. The preprocessing include silence removal, pre-emphasis, normalization and windowing so it is an important phase to get pure signal which is used in the next stage (feature extraction). The wave files (male, female) and the music file which are used in this paper have sample rate 48000; bit resolution 16 bit and mono channel. The wave files of this paper are taken from the Berlin dataset and RAVDESS dataset.