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.
목차
Abstract 1. INTRODUCTION 2. SELECTION RULES AND EXPERIMENTAL DATA 2.1 Training Data 2.2 Candidates for Analysis 2.3 Methodology 3. RESULTS OF RESEARCH 3.1 Dynamics 3.2 Tonal Balance & Roots 3.3 Tonal-Noisy Balance 3.4 Application and Algorithm Learning Method 4. CONCLUSION ACKNOWLEDGEMENT REFERENCES
국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
설립연도
2009
분야
공학>공학일반
소개
본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.
간행물
간행물명
International Journal of Advanced Culture Technology(IJACT)
간기
계간
pISSN
2288-7202
eISSN
2288-7318
수록기간
2013~2025
등재여부
KCI 등재
십진분류
KDC 600DDC 700
이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 12 Number 3