• Title/Summary/Keyword: computer music

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Physical Modeling of Plucked String Based on Fixed Spatial Sampling Interval (고정된 공간 축 샘플링 간격을 적용한 뜯는 현악기의 현에 관한 물리적 모델링)

  • 강명수;김규년
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.1
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    • pp.3-12
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    • 2001
  • In physical modeling of plucked string instruments, the vibration of a string is typically simulated by the linear system. Currently the Digital Waveguides of J.O.Smith[1] are widely used to get a high quality sound of the plucked string instrument. He used the wave equation to derive the Digital Waveguides and emphasized the time variable. In this thesis, new model of plucked string is proposed to improve the sound quality emphasizing the spatial variable of the wave equation. In our model, we used the fixed sampling interval which is not dependent on the speed of the wave. So we could get more detailed description of wave movement by the time variable. As a result, the new model could produce a higher quality sound of plucked string instrument.

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Approximate Periods of Strings based on Distance Sum for DNA Sequence Analysis (DNA 서열분석을 위한 거리합기반 문자열의 근사주기)

  • Jeong, Ju Hui;Kim, Young Ho;Na, Joong Chae;Sim, Jeong Seop
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.2
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    • pp.119-122
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    • 2013
  • Repetitive strings such as periods have been studied vigorously in so diverse fields as data compression, computer-assisted music analysis, bioinformatics, and etc. In bioinformatics, periods are highly related to repetitive patterns in DNA sequences so called tandem repeats. In some cases, quite similar but not the same patterns are repeated and thus we need approximate string matching algorithms to study tandem repeats in DNA sequences. In this paper, we propose a new definition of approximate periods of strings based on distance sum. Given two strings $p({\mid}p{\mid}=m)$ and $x({\mid}x{\mid}=n)$, we propose an algorithm that computes the minimum approximate period distance based on distance sum. Our algorithm runs in $O(mn^2)$ time for the weighted edit distance, and runs in O(mn) time for the edit distance, and runs in O(n) time for the Hamming distance.

Development of EEG Signals Measurement and Analysis Method based on Timbre (음색 기반 뇌파측정 및 분석기법 개발)

  • Park, Seung-Min;Lee, Young-Hwan;Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.3
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    • pp.388-393
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    • 2010
  • Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.

Combining deep learning-based online beamforming with spectral subtraction for speech recognition in noisy environments (잡음 환경에서의 음성인식을 위한 온라인 빔포밍과 스펙트럼 감산의 결합)

  • Yoon, Sung-Wook;Kwon, Oh-Wook
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.5
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    • pp.439-451
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    • 2021
  • We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

Development of Smart Mirror System based on the Raspberry Pi (Raspberry Pi를 이용한 스마트 미러 개발)

  • Lin, Zhi-Ming;Kim, Chul-Won
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.2
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    • pp.379-384
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    • 2021
  • With people's continuous research and exploration in the field of artificial intelligence, more relatively mature artificial intelligence technology is applied in people's daily life. Mirrors are the most commonly used daily necessities in life, and it should be applied to artificial intelligence. The research results of this paper show that the smart mirror designed based on the raspberry pi displays weather, temperature, greetings, and has a human-mirror interaction function. The research method of this paper uses the Raspberry pi 3B + as the core controller and Google Assistant as the intelligent control. When connected to the network via Raspberry Pi's own WiFi, the mirror can automatically display and update time, weather and news information features. You can wake up the Google Assistant using keywords, then control the mirror to play music, remind the time, It implements the function of smart mirror voice interaction. Also, all the hardware used in this study is modular assembly. Later, it is convenient for user to assemble by himself later. It is suitable for market promotion at an affordable price.

Analysis on Service Robot Market based on Intelligent Speaker (지능형 스피커 중심의 서비스 로봇 시장 분석)

  • Lee, Seong-Hoon;Lee, Dong-Woo
    • Journal of Convergence for Information Technology
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    • v.9 no.5
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    • pp.34-39
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    • 2019
  • One of the words frequently mentioned in our society today is the smart machine. Smart machines are machines that contain smart or intelligent functions. These smart machines have recently been applied in our home environment. These are phenomena that occur as a result of smart home. In a smart home environment, smart speakers have moved away from traditional music playback functions and are now increasingly serving as interfaces to control devices, the various components of a smart home. In this study, the technology trends of domestic and foreign smart speaker market are examined, problems of current products are analyzed, and necessary core technologies are described. In the domestic smart speaker market, SKT and KT are leading the related industries, while major IT companies such as Amazon, Google and Apple are focusing on launching related products and technology development.

A technique to support the personalized learning based on the log data of piano chords practicing (피아노 코드 연습 데이터를 활용한 맞춤형 학습 지원)

  • Woosung, Jung;Eunjoo, Lee;Suah, Choe
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.1
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    • pp.191-201
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    • 2023
  • As Edutech arises which is integrating IT technology into education, many related attempts have been tried on music education area. The focus has been shifted from the teachers to the learners, and this makes the personalized learning emerge. The learner's proficiency is an essential factor to support the personalized learning. The chord fingering is an important technique in piano learning. In this paper, a personalized learning tool for piano chords has been suggested. And then, several utilization ways have been described by analyzing the chords patterns. Specifically, the difficulty of the chords and the proficiency of the learner are derived from the accumulated practicing log data of the users. More effective learning way of the chords has been presented through hierarchical clustering based on chords similarity. Furthermore, the suggested approach where only the practicing log data are used lessens the learner's burden to measure the proficiency and the chord's difficulty without additional efforts like taking tests.

A Study on the Effects and Application Cases of Education Using Metaverse in the Non-Face-To-Face Era (비대면 시대에 메타버스를 이용한 교육의 효과와 적용사례에 대한 연구)

  • Song, Eun-Jee
    • Journal of Practical Engineering Education
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    • v.14 no.2
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    • pp.361-366
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    • 2022
  • Recently, with the development of virtual and augmented reality technology, metaverse is emerging as a new paradigm that will lead the next-generation internet era, and social and economic activities are spreading around the game, entertainment, music, and content industries. Moreover, as non-face-to-face conversion accelerated after the outbreak of COVID-19, lifestyles and industrial sites are becoming untact and further rapidly becoming a metaverse. In particular, the application of metaverse to the education field is attracting attention because realistic classes using real-time voice conversations using avatars, 3D objects, and 360-degree images can increase immersion and overcome the limitations of distance education. This study examines the concept of metaverse and examines that education using metaverse can be an alternative that can increase the efficiency of education in the non-face-to-face era. In particular, it shows that it is effective in language education and suggests an actual metaverse-based Korea language education program.

Mask Estimation Based on Band-Independent Bayesian Classifler for Missing-Feature Reconstruction (Missing-Feature 복구를 위한 대역 독립 방식의 베이시안 분류기 기반 마스크 예측 기법)

  • Kim Wooil;Stern Richard M.;Ko Hanseok
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.2
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    • pp.78-87
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    • 2006
  • In this paper. we propose an effective mask estimation scheme for missing-feature reconstruction in order to achieve robust speech recognition under unknown noise environments. In the previous work. colored noise is used for training the mask classifer, which is generated from the entire frequency Partitioned signals. However it gives a limited performance under the restricted number of training database. To reflect the spectral events of more various background noise and improve the performance simultaneously. a new Bayesian classifier for mask estimation is proposed, which works independent of other frequency bands. In the proposed method, we employ the colored noise which is obtained by combining colored noises generated from each frequency band in order to reflect more various noise environments and mitigate the 'sparse' database problem. Combined with the cluster-based missing-feature reconstruction. the performance of the proposed method is evaluated on a task of noisy speech recognition. The results show that the proposed method has improved performance compared to the Previous method under white noise. car noise and background music conditions.

Development of a Sound Art Programming Course for Non-Majors (비전공자를 위한 사운드 아트 프로그래밍 교과목 개발)

  • Kwon Hyunwoo
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.4
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    • pp.71-79
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    • 2024
  • This study developed a sound art programming course using pure data to foster computational thinking and convergence of art and technology in college students who are non-computer majors. This paper presents an example of operating a curriculum that designed and developed a sound art-centered music programming subject using Pure Data, derives educational outcomes and improvement measures for classes, and presents a creative convergence education program of technology and art. It has a purpose. For the study, we looked at examples of educational programs that combine art and technology, as well as pure data and sound art, and based on this, we designed and developed a sound art programming course for non-majors. The curriculum was operated based on the developed subjects, and the results showed increased interest in programming through art and technology convergence classes, active class participation through autonomous choice, creation of a new perspective on art, improvement of computational thinking skills, collaboration and communication. The educational effect of ability enhancement was confirmed. We expect that this study will be able to present a new perspective on the convergence education of art and technology, including artistic diversity and understanding of new media according to the development of media.