Papers

Self-supervised Complex Network for Machine Sound Anomaly Detection

International Conference
2021~
작성자
한혜원
작성일
2021-08-30 11:06
조회
1713
Authors : Miseul Kim, Minh-Tri Ho, Hong-Goo Kang

Year : 2021

Publisher / Conference : EUSIPCO

Research area : Audio Signal Processing, Anomaly Detection

In this paper, we propose an anomaly detection algorithm for machine sounds with a deep complex network trained by self-supervision. Using the fact that phase continuity information is crucial for detecting abnormalities in time-series signals, our proposed algorithm utilizes the complex spectrum as an input and performs complex number arithmetic throughout the entire process. Since the usefulness of phase information can vary depending on the type of machine sound, we also apply an attention mechanism to control the weights of the complex and magnitude spectrum bottleneck features depending on the machine type. We train our network to perform a self-supervised task that classifies the machine identifier (id) of normal input sounds among multiple classes. At test time, an input signal is detected as anomalous if the trained model is unable to correctly classify the id. In other words, we determine the presence of an anomality when the output cross-entropy score of the multiclass identification task is lower than a pre-defined threshold. Experiments with the MIMII dataset show that the proposed algorithm has a much higher area under the curve (AUC) score than conventional magnitude spectrum-based algorithms.
전체 355
335 Domestic Conference Hwayeon Kim, Hong-Goo Kang "Band-Split based Dual-Path Convolution Recurrent Network for Music Source Separation" in 2023년도 한국음향학회 춘계학술발표대회 및 제38회 수중음향학 학술발표회, 2023
334 International Conference Zhenyu Piao, Miseul Kim, Hyungchan Yoon, Hong-Goo Kang "HappyQuokka System for ICASSP 2023 Auditory EEG Challenge" in ICASSP, 2023
333 International Conference Byeong Hyeon Kim, Hyungseob Lim, Jihyun Lee, Inseon Jang, Hong-Goo Kang "Progressive Multi-Stage Neural Audio Codec with Psychoacoustic Loss and Discriminator" in ICASSP, 2023
332 International Conference Hyungseob Lim, Jihyun Lee, Byeong Hyeon Kim, Inseon Jang, Hong-Goo Kang "End-to-End Neural Audio Coding in the MDCT Domain" in ICASSP, 2023
331 International Conference Miseul Kim, Zhenyu Piao, Jihyun Lee, Hong-Goo Kang "Style Modeling for Multi-Speaker Articulation-to-Speech" in ICASSP, 2023
330 International Journal Jinyoung Lee, Hong-Goo Kang "Real-Time Neural Speech Enhancement Based on Temporal Refinement Network and Channel-Wise Gating Methods" in Digital Signal Processing, vol.133, 2023
329 International Journal Taemin Kim, Yejee Shin, Kyowon Kang, Kiho Kim, Gwanho Kim, Yunsu Byeon, Hwayeon Kim, Yuyan Gao, Jeong Ryong Lee, Geonhui Son, Taeseong Kim, Yohan Jun, Jihyun Kim, Jinyoung Lee, Seyun Um, Yoohwan Kwon, Byung Gwan Son, Myeongki Cho, Mingyu Sang, Jongwoon Shin, Kyubeen Kim, Jungmin Suh, Heekyeong Choi, Seokjun Hong, Huanyu Cheng, Hong-Goo Kang, Dosik Hwang & Ki Jun Yu "Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces" in Nature Communications, vol.13, 2022
328 International Journal Jinyoung Lee, Hong-Goo Kang "Two-Stage Refinement of Magnitude and Complex Spectra for Real-Time Speech Enhancement" in IEEE Signal Processing Letters, vol.29, pp.2188-2192, 2022
327 Domestic Conference Hyungseob Lim, Hong-Goo Kang, Inseon Jang "엔트로피 모델을 활용한 심층 신경망 기반 오디오 압축 모델 최적화" in 한국방송·미디어공학회 2022년 하계학술대회, 2022
326 International Conference Hyeon-Kyeong Shin, Hyewon Han, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang "Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting" in INTERSPEECH (*Best Student Paper Finalist), 2022