• Title/Summary/Keyword: Music Algorithm

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Study on the song title query by humming melody information (허밍 운율정보를 이용한 곡목 검색 기술)

  • Lee Ji-Yeoun;Hahn Min-Soo
    • MALSORI
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    • no.44
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    • pp.131-143
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    • 2002
  • Music query by humming is a challenging problem since the humming signal inevitably contains much variation and inaccuracy. In this paper, we suggest an algorithm for querying a wanted song from music database by humming its melody. In order to suit or adapt the inaccurate peoples humming, a new melody representation technique is proposed. Our algorithm is basically a pitch and duration information-based one and performs fairly well. 85% of correct query rate of the song is achieved for the top 3 matches when tested with 20 songs.

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Note Tracking and Localization Algorithm for Interactive Rhythm-based Music Player (리듬기반 인터액티브 음악 플레이어를 위한 음표 위치 추적 알고리즘)

  • Kim, Jae-Hong;Park, Jae-Sung;Lee, Jun-Seong;Cha, Dong-Hoon;Kim, Joung-Hyun
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.482-486
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    • 2009
  • Conventional music players offer simple replay and one way entertainment. The paper presents an algorithm to extract, within a digitally recorded music file, the temporal information of a sequence of target notes (i.e. melody). We assume to have the score (e.g. MIDI or printed score), and using this information, it becomes possible to first sequentially predict the probable location of the target notes. However, recorded music is hardly performed according to the score, especially temporally. Thus, additional analysis is carried out to hone in on the exact location of the target note from the initially predicted location. This prediction and correction process is repeated to find one note after another. This allows us to develop an interactive music player that is enacted by rhythmic interaction, and induce a new user experience, i.e. as if one is playing the music oneself.

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Real Time AOA Estimation Using Analog Neural Network Model (아날로그 신경망 모델을 이용한 실시간 도래방향 추정 알고리즘의 개발)

  • Jeong, Jung-Sik
    • Journal of Navigation and Port Research
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    • v.27 no.4
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    • pp.465-469
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    • 2003
  • It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

A Study on Music Summarization (음악요약 생성에 관한 연구)

  • Kim Sung-Tak;Kim Sang-Ho;Kim Hoi-Rin;Choi Ji-Hoon;Lee Han-Kyu;Hong Jin-Woo
    • Journal of Broadcast Engineering
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    • v.11 no.1 s.30
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    • pp.3-14
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    • 2006
  • Music summarization means a technique which automatically generates the most importantand representative a part or parts ill music content. The techniques of music summarization have been studied with two categories according to summary characteristics. The first one is that the repeated part is provided as music summary and the second provides the combined segments which consist of segments with different characteristics as music summary in music content In this paper, we propose and evaluate two kinds of music summarization techniques. The algorithm using multi-level vector quantization which provides a repeated part as music summary gives fixed-length music summary is evaluated by overlapping ration between hand-made repeated parts and automatically generated summary. As results, the overlapping ratios of conventional methods are 42.2% and 47.4%, but that of proposed method with fixed-length summary is 67.1%. Optimal length music summary is evaluated by the portion of overlapping between summary and repeated part which is different length according to music content and the result shows that automatically-generated summary expresses more effective part than fixed-length summary with optimal length. The cluster-based algorithm using 2-D similarity matrix and k-means algorithm provides the combined segments as music summary. In order to evaluate this algorithm, we use MOS test consisting of two questions(How many similar segments are in summarized music? How many segments are included in same structure?) and the results show good performance.

Development of Parameter Extraction Algorithm and Software Simulator For a Digital Music FM Synthesis (FM 방식의 디지털 악기음 합성을 위한 소프트웨어 시뮬레이터 및 파라미터 추출 알고리즘 개발)

  • Joon Yul Joo
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.3
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    • pp.24-38
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    • 1994
  • In this paper we develop the software simulator written in a C language for a frequency modulation synthesis and the approximate range of parameters, for a musically satisfactory timbre, obtained by using the software simulator will be applied to develop an algorithm for parameter extraction. For a frequency modulation synthesis, we also develop an algorithm for parameter extraction through waveform analysis in the time domain as well as spectrum analysis using a FFT in the frequency domain. To verify the validity of the developed algorithm as well as software simulator experimentally, we extract parameters for the several music instruments using the suggested algorithm and analyze the synthesized sound by applying the parameters to the software simulator. The evaluation of the synthesized sound is first done by listening the sound directly as a subjective testing. Secondly, to evaluate the synthesized sound objectively with an engineering sense, we compare the synthesized sound with an original one in a time domain and a frequency domain.

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Blind Beamforming Equalization System Based on MUSIC Algorithm (MUSIC 알고리즘 기반 블라인드 빔포밍 등화 시스템)

  • Kim, Yongguk;Lee, Seung Hwan;Shin, Dong Jin;Ryu, Heung-Gyoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.1
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    • pp.64-72
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    • 2013
  • Blind equalization is a technique that equalizes the received signals without the training sequence. Because of the absence of training sequence, we can increase the bandwidth efficiency due to the blind equalization system. And we must use the blind equalization for removing the ISI in mobile satellite communication receiver. ISI occurs due to mobility of users in mobile satellite communications. Blind equalization is suitable for the mobile satellite communication channels. In this blind equalization, it's very important to improve BER performance to apply the mobile satellite communication system. In this paper, we propose the blind beamforming equalization system using the beamforming, MUSIC algorithm and coordinate change method. We were confirmed by the simulation that the proposed system improves the BER performance.

Korean Traditional Music Melody Generator using Artificial Intelligence (인공지능을 이용한 국악 멜로디 생성기에 관한 연구)

  • Bae, Jun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.7
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    • pp.869-876
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    • 2021
  • In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

DOA estimation of signals using non-parametric algorithm (Non-parametric 알고리즘을 이용한 신호의 DOA 추정)

  • 이광식;문성익;양두영
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.121-124
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    • 2003
  • In this paper, the non-parametric algorithm to estimate DOA(Direction Of Arrival) of signals is proposed and compared with the multidimensional MUSIC algorithm. This non-parametric algorithm with regularizing sparsity constraints achieves super-resolution and noise suppression, effectively. Also, this algorithm offers the increased resolution and significantly reduced sidelobes.

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Spatial Spectrum Estimation of Incident Signal Via Measured Array Manifold (측정 Array Manifold를 적용한 입사 신호의 공간 스펙트럼 추정)

  • 강흥용;이성윤;김영수;김창주;박한규
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.3
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    • pp.223-230
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    • 2004
  • A method for measuring array manifold which is the array antenna response of incident signal is presented. Array manifold measurement procedure by the presented method is explained for UCA(Uniform Circular Array), and spatial spectrum of 300 ㎒ tone signal incident on UCA is estimated by MUSIC algorithm in which spatial spectrum peak is searched with measured array manifold. Spatial spectrum estimation using array manifold measured by the proposed method shows superior performance to calculated array manifold.