DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 남주한 | - |
dc.contributor.author | Kim, Jongsoo | - |
dc.contributor.author | 김종수 | - |
dc.date.accessioned | 2024-07-30T19:30:47Z | - |
dc.date.available | 2024-07-30T19:30:47Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1096186&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/321401 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 문화기술대학원, 2024.2,[iv, 35 p. :] | - |
dc.description.abstract | Audio fingerprinting systems have evolved over time through frequency-analysis techniques, and have recently shown significantly improved performance in noisy environments through deep neural networks. However, these systems work well for identifying music played in specific spaces, but show lower performance in broadcast monitoring tasks. A major problem is that both deep neural network-based and frequency analysis-based systems often fail to detect music segments, mistaking them for non-musical content, primarily due to speech noise overpowering the music in broadcast audio. To address this, our study employed a pre-trained source separation model to remove vocals before feeding the query audio into the fingerprint extraction model, enhancing the performance of the broadcast monitoring system. Furthermore, We fine-tuned the source separation model to optimize it for speech removal. To do this, we customized the training dataset by replacing the vocal source with speech source. As a result, we improved the speech removal performance, boosting the performance of the broadcast monitoring system. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | 오디오 지문▼a심층신경망▼a목소리 제거▼a음원 분리▼a미세 조정 | - |
dc.subject | Audio fingerprinting▼aDeep neural network▼aSpeech removal▼aSource separation▼aFine-tuning | - |
dc.title | Neural audio fingerprinting for broadcast monitoring with source separation | - |
dc.title.alternative | 음원 분리를 적용한 방송 모니터링용 신경망 기반 오디오 핑거프린팅 기법 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :문화기술대학원, | - |
dc.contributor.alternativeauthor | Nam, Juhan | - |
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