earticle

영어

This study presents five selection rules for training algorithms to extract audio sources from noise. The five rules are Dynamics, Roots, Tonal Balance, Tonal-Noisy Balance, and Stereo Width, and the suitability of each rule for sound extraction was determined by spectrogram analysis using various types of sample sources, such as environmental sounds, musical instruments, human voice, as well as white, brown, and pink noise with sine waves. The training area of the algorithm includes both melody and beat, and with these rules, the algorithm is able to analyze which specific audio sources are contained in the given noise and extract them. The results of this study are expected to improve the accuracy of the algorithm in audio source extraction and enable automated sound clip selection, which will provide a new methodology for sound processing and audio source generation using noise.