• Title/Summary/Keyword: music signal

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High-Resolution Algorithm for Direction Finding of Multiple Incoherent Plane Waves (다중 인코히어런트 평면파의 도래각 추정을 위한 고분해능 알고리즘)

  • 김영수;이성윤
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.9A
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    • pp.1322-1328
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    • 1999
  • In this paper, we propose a Multiple Signal Classification(MUSIC) in conjunction with signal enhancement (SE-MUSIC) for solving the direction-of-arrival estimation problem of multiple incoherent plane waves incident on a uniform linear array. The proposed SE-MUSIC algorithms involve the following main two-step procedure : ( i )to find the enhanced matrix that possesses the prescribed properties and which lies closest to a given covariance matrix estimate in the Frobenius norm sense and (ii) to apply the MUSIC to the enhanced matrix. Simulation results are illustrated to demonstrate the better resolution and statistical performance of the proposed method than MUSIC at lower SNR.

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Feature Parameter Extraction and Analysis in the Wavelet Domain for Discrimination of Music and Speech (음악과 음성 판별을 위한 웨이브렛 영역에서의 특징 파라미터)

  • Kim, Jung-Min;Bae, Keun-Sung
    • MALSORI
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    • no.61
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    • pp.63-74
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    • 2007
  • Discrimination of music and speech from the multimedia signal is an important task in audio coding and broadcast monitoring systems. This paper deals with the problem of feature parameter extraction for discrimination of music and speech. The wavelet transform is a multi-resolution analysis method that is useful for analysis of temporal and spectral properties of non-stationary signals such as speech and audio signals. We propose new feature parameters extracted from the wavelet transformed signal for discrimination of music and speech. First, wavelet coefficients are obtained on the frame-by-frame basis. The analysis frame size is set to 20 ms. A parameter $E_{sum}$ is then defined by adding the difference of magnitude between adjacent wavelet coefficients in each scale. The maximum and minimum values of $E_{sum}$ for period of 2 seconds, which corresponds to the discrimination duration, are used as feature parameters for discrimination of music and speech. To evaluate the performance of the proposed feature parameters for music and speech discrimination, the accuracy of music and speech discrimination is measured for various types of music and speech signals. In the experiment every 2-second data is discriminated as music or speech, and about 93% of music and speech segments have been successfully detected.

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Design of 2D MUSIC Algorithm to Reduce Computational Burden (연산량 감소를 위한 2D MUSIC 알고리즘 설계)

  • Choi, Yun Sub;Jin, Mi Hyun;Choi, Heon Ho;Lee, Sang Jeong;Park, Chansik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37C no.11
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    • pp.1077-1083
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    • 2012
  • The jamming countermeasures in GNSS includes anti-jamming technique and jammer localization technique. In both techniques, direction of jamming signal is important and generally the MUSIC algorithm is used to find the direction of jamming signal. The MUSIC is super-resolution algorithm for detecting incident direction of signal. But, the search time of MUSIC algorithm is too long because all candidates of incidence angle are searched. This paper proposes the new method that has less computational burdens and therefore faster than the conventional MUSIC algorithm. The proposed method improves performance speed by reducing unnecessary calculations. In the proposed method, the cost function of conventional MUSIC algorithm is decomposed into the sum of squares and if the partial sum of cost function is larger than the minimum cost function so far, then the candidate is rejected and next candidates are searched. If the computed cost function is less than the minimum cost function so far, the minimum cost function so far is replaced with newly computed value. The performance of the proposed method was compared with the conventional MUSIC algorithm using the simulation. The accuracy of the estimaed direction of jamming signal was same as the conventional MUSIC while the search speed of the proposed method was 1.15 times faster than the conventional MUSIC.

Lighting Control using Frequency Analysis of Music (음악의 주파수 분석을 이용한 조명 제어)

  • HwangBo, Seok;Chun, Sung-Yong;Gang, So-Yeung;Lee, Chan-Su
    • Journal of Korea Multimedia Society
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    • v.16 no.11
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    • pp.1325-1337
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    • 2013
  • Music affects sensitivity and emotion of human, emotional power of the music has been applied to various fields. Especially, to visualize as well as listen to music is able to create various atmosphere. In this paper, we proposed sensitivity control system for interaction with people to merge music and lighting. Because existing FT(Fourier Transform) has not information about the time, to analyze information of changed signal according to the time is difficult. In order to solve such a problem, we use STFT(Short Time Fourier Transform) method to analyze music signal. and also, we classified music for three genre and compared the frequency characteristics according to genre, and control the color, brightness of LED light based on the frequency components within analysis range. Unlike existing LED lighting control study using music, we had color control of emotional lighting and brightness control using variation amount of music signal in this paper. Proposed lighting control system will be able to utilize various industry fields as well as emotional lighting.

A Threshold Adaptation based Voice Query Transcription Scheme for Music Retrieval (음악검색을 위한 가변임계치 기반의 음성 질의 변환 기법)

  • Han, Byeong-Jun;Rho, Seung-Min;Hwang, Een-Jun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.2
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    • pp.445-451
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    • 2010
  • This paper presents a threshold adaptation based voice query transcription scheme for music information retrieval. The proposed scheme analyzes monophonic voice signal and generates its transcription for diverse music retrieval applications. For accurate transcription, we propose several advanced features including (i) Energetic Feature eXtractor (EFX) for onset, peak, and transient area detection; (ii) Modified Windowed Average Energy (MWAE) for defining multiple small but coherent windows with local threshold values as offset detector; and finally (iii) Circular Average Magnitude Difference Function (CAMDF) for accurate acquisition of fundamental frequency (F0) of each frame. In order to evaluate the performance of our proposed scheme, we implemented a prototype music transcription system called AMT2 (Automatic Music Transcriber version 2) and carried out various experiments. In the experiment, we used QBSH corpus [1], adapted in MIREX 2006 contest data set. Experimental result shows that our proposed scheme can improve the transcription performance.

Chopping Frequency Extraction of JEM Signal Using MUSIC Algorithm (MUSIC 알고리즘을 이용한 JEM 신호의 Chopping 주파수 추출)

  • Song, Won-Young;Kim, Hyung-Ju;Kim, Sung-Tai;Shin, In-Seon;Myung, Noh-Hoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.3
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    • pp.252-259
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    • 2019
  • Jet engine modulation(JEM) signals are widely used in the field of target recognition along with high-range resolution profile and inverse synthetic aperture radar because they provide specific information of the jet engine. To obtain the number of blades of the jet engine, the chopping frequency proportional to the number of blades must be extracted. In the conventional chopping frequency extraction method, an initial threshold value is defined and a method of detecting the chopping peak is used. However, this detection method takes time depending on the signal due to repetitive detection. Thus, in this study, we proposed to extract the chopping frequency using MUltiple SIgnal Classification(MUSIC) algorithm. We applied the MUSIC algorithm to a given JEM signal to find the chopping frequency and determine the blade number candidates. We also applied the MUSIC algorithm to other chopping frequency extractions to determine the score of the candidate groups. Unlike the conventional detection algorithm, which requires repetitive frequency detection, MUSIC algorithm quickly detects the accurate chopping frequency and reduces the calculation time.

A Study on Signal Analysis of Korean Traditional Music Instrument, Kayakeum and Piri (국악 악기 가야금과 피리의 신호 분석에 관한 연구)

  • Lee Sang-Min;Lee Jong-Seok;Lee Kwang-Hyung
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.247-250
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    • 1999
  • Like any other music, Korean traditional music make a beautiful compound melody of many music instruments. In this paper, we separate melody especially played by two instruments, that is Kayakeum, Piri(Korean pipe) analysing each audio signal. Kayakeum, Piri have a unique frequency component for each sound height. Therefore each melody of them can be expressed into each sheet of notation separately and MIDI codes. We expect that this paper will benefit all the people studying and instructing Korean music.

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A Study on Signal Estimation of Modified Beamformer Method using Perturbation Covariance Matrix (섭동공분산행렬을 이용한 수정 빔형성기 방법의 신호 추정에 대한 연구)

  • Lee, Kwan-Hyeong;Cho, Tae-Jun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.4
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    • pp.333-339
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    • 2017
  • Transmission signal in wireless environment receives a signal in which a source signal, interference, and noise are mixed. The goal of this study is to estimate the desired signal from the received signal. In this paper, we have studied a method correctly estimating a target in spatial by modified beamformer method. The modified bemaformer uses an adaptive array antenna and perturbation matrix to obtain the optimal weight, and estimate the desired signal by radiating the beam in spatial. We estimate a desired signal of the target by improving resolution with the modified beamformer method which does not have complicated calculation amount. Through simulation, we compare and analyze the modified beamformer method and the MUSIC method with good resolution. In result of simulation, we showed that modified beamformer method has better resolution of 10degree than classical beamformer method and showed similar performance as the MUSIC method. The resolution of this paper was estimated to be about 5 degrees.

Content-Based Genre Classification Using Climax Extraction in Music (음악의 클라이맥스 추출을 이용한 내용 기반 장르 분류)

  • Ko, Il-Ju;Chung, Myoung-Bum
    • Journal of Korea Multimedia Society
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    • v.10 no.7
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    • pp.817-826
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    • 2007
  • The existing a music genre classification research used signal feature of the part which gets 20 seconds interval of the random or the $40%{\sim}45%$ after in the music. This paper propose it to increase the accuracy of existing research to classify music genre using climax part in the music. Generally the music is divided to three parts; introduction, progress and climax. And the climax is the part which the music emphasizes and expresses the feature of the music best. So, we can get efficient result if the climax is used, when the music classify. We can get the climax in the music finding the tempo and node which uses FFT and the maximum waveform from each node. In this paper, we did a genre classification experiment which uses existing research method and proposing method. The existing method expressed 47% accuracy. And proposing method expressed 56% accuracy which is improved than existing method.

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A Study on Radar Signal Model for Calculation of RCS Using MUSIC Algorithm (레이더 반사단면적 계산을 위한 레이더 신호모델에 관한 연구)

  • Jeong Junng-Sik;Pang Tian-Ting;Jong Jae-Yong;Kim Chul-Seung;Yang Won-Jae;Ahn Young-Sup
    • Proceedings of KOSOMES biannual meeting
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    • 2005.11a
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    • pp.75-78
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    • 2005
  • The detectability of radar depends on RCS(radar cross section). The RCS for complex radar targets may be only approximately calculated by using low-frequency or high-frequency scattering methods, while the RCS for simple radar targets can be exactly obtained by applying on eigen-function method. However, the conventional methods for calculation of RCS are computationally complex. We propose an radar signal model for RCS calculation by MUSIC algorithm In this research, it is assumed that the radar target is considered as a ring of scatterers. The amplitudes of scatterers may be statistically distributed. As the result, the radar signal model is proposed to use MUSIC, and the RCS is calculated by a simple linear algebraic method.

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