• Title/Summary/Keyword: Music Algorithm

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The recognition of Printed Music Score and Performance Using Computer Vision system (컴퓨터 비젼 시스템에 의한 인쇄악보의 인식과 연주)

  • 이명우;최종수
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.22 no.5
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    • pp.10-16
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    • 1985
  • In this paper, a computer vision system, which catches printed music score image using CCTV camera and microcomputer, and then recognizes the image and performs tar music with speaker, is discussed. Integral projection method is adopted for feature detection and recognition of the music score image. The range of recognition is con(ined to staffs, perpen-dicular lines and musical notes including chord notes among the various kinds of elements of music score. The practical recognition algorithm considering noises, the preprocessing processes getting rid of noises are also showed, and simple hardware system playing chord is made, In the results, good recognition ratio and performance are obtained.

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Collaborative Filtering and Genre Classification for Music Recommendation

  • Byun, Jeong-Yong;Nasridinov, Aziz
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.693-694
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    • 2014
  • This short paper briefly describes the proposed music recommendation method that provides suitable music pieces to a listener depending on both listeners' ratings and content of music pieces. The proposed method consists of two methods. First, listeners' ratings prediction method is a combination the traditional user-based and item-based collaborative filtering methods. Second, genre classification method is a combination of feature extraction and classification procedures. The feature extraction step obtains audio signal information and stores it in data structure, while the second one classifies the music pieces into various genres using decision tree algorithm.

Music Therapy Counseling Recommendation Model Based on Collaborative Filtering (협업 필터링 기반의 음악 치료 상담 추천 모델)

  • Park, Seong-Hyun;Kim, Jae-Woong;Kim, Dong-Hyun;Cho, Han-Jin
    • Journal of the Korea Convergence Society
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    • v.10 no.9
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    • pp.31-36
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    • 2019
  • Music therapy, a field that convergence music and treatment, which play a fundamental role in personality formation, possesses diverse and complex treatment methods. Music therapists in charge of music therapy may experience the same phenomenon as countertransference in consultation with clients. In addition, experiencing psychological burnout, there are many difficulties in reaching the final goal of music therapy. In this paper, we provide a collaborative filtering-based music therapy consultation data recommendation model for smooth music therapy consultation with clients who visited for music therapy. The proposed model grasps the similarity between the conventional consultation data and the new consultant data through the euclidean distance algorithm. This is to recommend similar consultation materials. Since music therapists can provide optimal consultation materials for consultants who need music therapy, smooth consultation is expected.

Multiple octave-band based genre classification algorithm for music recommendation (음악추천을 위한 다중 옥타브 밴드 기반 장르 분류기)

  • Lim, Shin-Cheol;Jang, Sei-Jin;Lee, Seok-Pil;Kim, Moo-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.7
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    • pp.1487-1494
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    • 2011
  • In this paper, a novel genre classification algorithm is proposed for music recommendation system. Especially, to improve the classification accuracy, the band-pass filter for octave-based spectral contrast (OSC) feature is designed considering the psycho-acoustic model and actual frequency range of musical instruments. The GTZAN database including 10 genres was used for 10-fold cross validation experiments. The proposed multiple-octave based OSC produces better accuracy by 2.26% compared with the conventional OSC. The combined feature vector based on the proposed OSC and mel-frequency cepstral coefficient (MFCC) gives even better accuracy.

Direction-of-Arrival Estimation : Signal Eigenvector Method(SEM) (도래각 추정 : 신호 고유벡터 알고리즘)

  • 김영수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.12
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    • pp.2303-2312
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    • 1994
  • A high resolution algorithm is presented for resolving multiple narrowband plane waves that are incident on an equispaced linear array. To overcome the deleterious effects due to coherent sources, a number of noise-eigenvector-based approaches have been proposed for narrowband signal processing. For differing reasons, each f these methods provide a less than satisfactory resolution of the coherency problem. The proposed algorithm makes use of fundamental property possessed by those eigenvectors of the spatial covariance matrix that are associated with eigenvalues that are larger than the sensor noise level. This property is then used to solve the incoherent and coherent sources incident on an equispaced linear array. Simulation results are shown to illustrate the high resolution performance achieved with this new approach relative to that obtained with MUSIC and spatial smoothed MUSIC.

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Music Recommendation Technique Using Metadata (메타데이터를 이용한 음악 추천 기법)

  • Lee, Hye-in;Youn, Sung-dae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.75-78
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    • 2018
  • Recently, the amount of music that can be heard is increasing exponentially due to the growth of the digital music market. Because of this, online music service users have had difficulty choosing their favorite music and have wasted a lot of time. In this paper, we propose a recommendation technique to minimize the difficulty of selection and to reduce wasted time. The proposed technique uses an item - based collaborative filtering algorithm that can recommend items without using personal information. For more accurate recommendation, the user's preference is predicted by using the metadata of the music source and the top-N music with high preference is finally recommended. Experimental results show that the proposed method improves the performance of the proposed method better than it does when the metadata is not used.

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Computational Complexity Analysis of Cascade AOA Estimation Algorithm Based on FMCCA Antenna

  • Kim, Tae-yun;Hwang, Suk-seung
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.2
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    • pp.91-98
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    • 2022
  • In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

Design of MUSIC-based DoA Estimator for Bluetooth Applications (Bluetooth 응용을 위한 MUSIC 알고리즘 기반 DoA 추정기의 설계)

  • Kim, Jongmin;Oh, Dongjae;Park, Sanghoon;Lee, Seunghyeok;Jung, Yunho
    • Journal of IKEEE
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    • v.24 no.1
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    • pp.339-346
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    • 2020
  • In this paper, we propose an angle estimator that is designed to be applied to Bluetooth low-power application technology based on multiple signal classification (MUSIC) algorithm, and present the result of implementation in FPGA. The MUSIC algorithm is designed for H/W high-speed design because it requires a lot of calculations due to high accuracy, and the snapshot variable is designed to cope with various resolution requirements of indoor systems. As a result of the implementation with Xilinx zynq-7000, it was confirmed that 9,081 LUTs were implemented, and it was designed to operate at =the operating frequency of 100MHz.

Automatic Generation of Serial Music Using Space-Filling Curves (공간 채움 곡선을 이용한 자동 음열 음악 작곡 방법)

  • Yoo, Min-Joon;Lee, In-Kwon
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.733-738
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    • 2008
  • Serial Music, introduced by A. Sch nberg, is a one of the important composition techniques. This music style has features of pantonality and atonality, so it generates unique atmosphere of modern music. In this paper, we introduce an method of generating serial music using mathematical algorithm. This method generates music that satisfy the requirement that the number of pitches belonged to each pitch class are exactly same, though the requirement is less strict than Sch nberg's definition. To do this, our method uses space-filling curves traversing the twelve tone matrix, which is constructed by the serial series, its inversion and its transpose. Using these curves, we can generate a music that has all notes in the matrix exactly once and adequate repeatness because of the curve's locality. Result music, therefore, can be more suitable for people that are not familiar with modern music, while maintaining the features of pantonality and atonality. This paper also introduces a method of generating extended serial music that uses serialism of duration and dynamic of notes, using multi-dimensional space-filling curves.

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