• Title/Summary/Keyword: Onset Detection

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A Study on Visualization of Musical Rhythm Based on Music Information Retrieval (Music Information Retrieval(MIR)을 활용한 음악적 리듬의 시각화 연구 -Onset 검출(Onset Detection) 알고리즘에 의한 시각화 어플리케이션)

  • Che, Swann
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.1075-1080
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    • 2009
  • 이 글은 Music Information Retrieval(MIR) 기법을 사용하여 오디오 콘텐츠의 리듬 정보를 자동으로 분석하고 이를 시각화하는 방법에 대해 다룬다. 특히 MIR을 활용한 간단한 시각화(sound visualization) 어플리케이션을 소개함으로써 음악 정보 분석이 디자인, 시각 예술에서 다양하게 활용될 수 있음을 보이고자 한다. 음악적 정보를 시각 예술로 담아내려는 시도는 20세기 초 아방가르드 화가들에 의해 본격적으로 시작되었다. 80년대 이후에는 컴퓨터 기술의 급속한 발전으로 사운드와 이미지를 디지털 영역에서 쉽게 하나로 다룰 수 있게 되었고, 이에 따라 다양한 오디오 비주얼 예술작품들이 등장하였다. MIR은 오디오 콘텐츠로부터 음악적 정보를 분석하는 DSP(Digital Signal Processing) 기술로 최근 디지털 콘텐츠 시장의 확장과 더불어 연구가 활발히 진행되고 있다. 특히 웹이나 모바일에서는 이미 다양한 상용 어플리케이션이 적용되고 있는데 query-by-humming과 같은 음악 인식 어플리케이션이 대표적인 경우이다. 이 글에서는 onset 검출(onset detection)을 중심으로 음악적 리듬을 분석하는 알고리즘을 살펴보고 기본적인 조형원리에 따라 이를 시각화하는 어플리케이션의 예를 소개한다.

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Detection of Onset and Offset Time of Muscle Activity in Surface EMG using the Kalman Smoother

  • Lee Jung-Hoon;Lee Hyun-Sook;Lee Young-Hee;Yoon Young-Ro
    • Journal of Biomedical Engineering Research
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    • v.27 no.3
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    • pp.131-141
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    • 2006
  • A visual decision by clinical experts like physical therapists is a best way to detect onset and offset time of muscle activation. The current computer-based algorithms are being researched toward similar results of clinical experts. The new algorithm in this paper has an ability to extract a trend from noisy input data. Kalman smoother is used to recognize the trend to be revealed from disorderly signals. Histogram of smoothed signals by Kalman smoother has a clear boundary to separate muscle contractions from relaxations. To verify that the Kalman smoother algorithm is reliable way to detect onset and offset time of muscle contractions, the algorithm of Robert P. Di Fabio (published in 1987) is compared with Kalman smoother. For 31 templates of subjects, an average and a standard deviation are compared. The average of errors between Di Fabio's algorithm and experts is 109 milliseconds in onset detection and 142 milliseconds in offset detection. But the average between Kalman smoother and experts is 90 and 137 milliseconds in each case. Moreover, the standard deviations of errors are 133 (onset) and 210 (offset) milliseconds in Di Fabio's one, but 48 (onset) and 55 (offset) milliseconds in Kalman smoother. As a result, the Kalman smoother is much closer to determinations of clinical experts and more reliable than Di Fabio's one.

Bayesian Onset Measure of sEMG for Fall Prediction (베이지안 기반의 근전도 발화 측정을 이용한 낙상의 예측)

  • Seongsik Park;Keehoon Kim
    • The Journal of Korea Robotics Society
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    • v.19 no.2
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    • pp.213-220
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    • 2024
  • Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.

Muscle Stiffness based Intent Recognition Method for Controlling Wearable Robot (착용형 로봇을 제어하기 위한 근경도 기반의 의도 인식 방법)

  • Yuna Choi;Junsik Kim;Daehun Lee;Youngjin Choi
    • The Journal of Korea Robotics Society
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    • v.18 no.4
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    • pp.496-504
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    • 2023
  • This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.

Onset Date of Forest Canopy Detected from MODIS Leaf Area Index

  • Kim, So-Hee;Kang, Sin-Kyu;Lim, Jong-Hwan
    • Journal of Ecology and Environment
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    • v.31 no.2
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    • pp.153-159
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    • 2008
  • The timing of the canopy phenology onset (CPO hereafter) indicates the initiation of the growing season, with rapid increases in exchange rates of carbon dioxide and water vapor between vegetation and atmosphere. The CPO is regarded as a potential indicator of ecosystem responses to global warming, but the CPO shows considerable spatial variation depending on the species composition and local temperature regime. at a given geographic location. In this study, we evaluated the utility of satellite observation data for detection of the timing of the CPO. Leaf area indices (LAI) obtained from the Moderate Resolution Imaging Spectrora-diometer (MODIS) were utilized to detect and map the onset dates from 2001 to 2006. The reliability of MODIS-based onset dates was evaluated with ground measured cherry blossom flowering data from national weather stations. The MODIS onset dates preceded the observed flowering dates by 8 days and were linearly related with a correlation coefficient of 0.58 (p < 0.05). In spite of the coarse spatial (1 km) and temporal (8 days) resolutions of MODIS LAI, the MODIS-based onset dates showed reasonable ability to predict flowering dates.

A Drum Onset Detection Scheme Based on Probabilistic Latent Component Analysis (확률적 은닉 성분 분석에 기반한 드럼 Onset 검출 방법)

  • Han, Byeong-jun;Kim, Yunjoo;Lee, Jangwoo;Kim, Minje;Lee, Kyogu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.11a
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    • pp.762-765
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    • 2010
  • 특정 시간에 동시 연주된 다수 음원의 onset 을 검출하기 위해서는 음원 분리 문제가 선결되어야 한다. 특히, 드럼과 같은 조음(?音) 악기 신호 검출 문제를 해결하기 위해서는 음원 분리 방법의 성능이 중요하다. 이에 본 연구에서는 효과적인 음원 분리 방법으로 알려진 확률적 은닉 성분 분석(PLCA) 방법에 기반한 주요 악기 신호의 onset 검출 방법을 제안한다. 효과적인 onset 검출을 위해, 첫째, 확률적 은닉 성분 분석으로 훈련 된 비음수 주파수 성분 중 최적의 성분을 선택하는 방법을 적용하고, 둘째, 드럼 악기 신호의 정확한 onset 검출을 위해 고안된 비음수 시계열 신호 threshold 방법을 적용한다. 실험에서는 제시된 방법을 이용하여 드럼의 주요 악기 신호 onset 검출 성능이 향상됨을 보인다.

An Onset Detection Scheme for Vocal Queries Based on Dynamic Expansible MLP (동적 확장 가능한 다중 계층 신경망에 기반한 음성 질의의 onset 검출 기법)

  • Han, Byeong-Jun;Rho, Seung-Min;Hwang, Een-Jun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06c
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    • pp.422-426
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    • 2007
  • 음성 질의에서 효율적으로 onset을 검출하기 위한 연구는 다양하게 이루어져 왔다. 특히 대부분의 연구는 확률론적 모델에서 큰 성과를 나타내고 있다. 그러나 이러한 모델들은 변화나 확장이 쉽지 않다는 단점을 가지고 있다. 본 논문에서는 동적 확장 가능한 다중 계층 신경망(Dynamic Expansible MLP)을 제안하여, 기존 방법론의 확장 가능성을 모색한다. 또한, 음성 질의의 onset을 검출하기 위해 MLP를 활용하기 위한 모델을 제시한다.

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Performance Evaluation of Speech Onset Representation Characteristic of Cochlear Implants Speech Processor using Spike Train Decoding (Spike Train Decoding에 기반한 인공와우 어음처리기의 음성시작점 정보 전달특성 평가)

  • Kim, Doo-Hee;Kim, Jin-Ho;Kim, Kyung-Hwan
    • Journal of Biomedical Engineering Research
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    • v.28 no.5
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    • pp.694-702
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    • 2007
  • The adaptation effect originating from the chemical synapse between auditory nerve and inner hair cell gives advantage in accurate representation of temporal cues of incoming speech such as speech onset. Thus it is expected that the modification of conventional speech processing strategies of cochlear implant(CI) by incorporating the adaptation effect will result in considerable improvement of speech perception performance such as consonant perception score. Our purpose in this paper was to evaluate our new CI speech processing strategy incorporating the adaptation effect by the observation of auditory nerve responses. By classifying the presence or absence of speech from the auditory nerve responses, i. e. spike trains, we could quantitatively compare speech onset detection performances of conventional and improved strategies. We could verify the effectiveness of the adaptation effect in improving the speech onset representation characteristics.

Comparison of Speech Onset Detection Characteristics of Adaptation Algorithms for Cochlear Implant Speech Processor (인공와우 어음처리방식을 위한 적응효과 알고리즘의 음성개시점 검출 특성 비교)

  • Choi, Sung-Jin;Kim, Jin-Ho;Kim, Kyung-Hwan
    • Journal of Biomedical Engineering Research
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    • v.29 no.1
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    • pp.25-31
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    • 2008
  • It is well known that temporal information, i.e speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.

Combustion Control and Symptom Detection on Self-excited Combustion Oscillation (자려 연소진동에 관한 연소제어와 징후의 검출)

  • Yang Young-Joon
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.7
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    • pp.1111-1122
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    • 2004
  • An idea to suppress the self-excited combustion oscillation was applied to the flames. The characteristics of unsteady combustion were examined and the unsteady combustion was driven by forced pulsating mixture supply that can modulate its amplitude and frequency. The self-excited combustion oscillation having weaker flow velocity fluctuation intensity than that of the forced pulsating supply can be suppressed by this method. The effects of the forced pulsation amplitude and frequency on controlling self-excited combustion oscillations were also investigated comparing with the steady mixture supply. The unsteady combustion used in this experiment plays an important role in controlling self-excited combustion oscillation. Symptoms of self-excited combustion oscillation were also studied in order to predict the onset of combustion oscillation before it proceeded to a catastrophic failure For the purpose, the unique measures to observe the onset of self-excited combustion oscillations based on the careful statistics of fluctuating properties in flames, such as pressure or emission of OH radicals, have been proposed.