• Title, Summary, Keyword: Music Selection

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A Music Recommendation Method Using Emotional States by Contextual Information

  • Kim, Dong-Joo;Lim, Kwon-Mook
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.10
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    • pp.69-76
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    • 2015
  • User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

An investigation of chroma n-gram selection for cover song search (커버곡 검색을 위한 크로마 n-gram 선택에 관한 연구)

  • Seo, Jin Soo;Kim, Junghyun;Park, Jihyun
    • The Journal of the Acoustical Society of Korea
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    • v.36 no.6
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    • pp.436-441
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    • 2017
  • Computing music similarity is indispensable in constructing music retrieval system. This paper focuses on the cover song search among various music-retrieval tasks. We investigate the cover song search method based on the chroma n-gram to reduce storage for feature DB and enhance search accuracy. Specifically we propose t-tab n-gram, n-gram selection method, and n-gram set comparison method. Experiments on the widely used music dataset confirmed that the proposed method improves cover song search accuracy as well as reduces feature storage.

A Study on the Necessity for the Music Composition in TV Documentaries - Focusing on In-depth Interviews with Music Directors at KBS.

  • Kim, Hyung-Jin
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.74-85
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    • 2020
  • In this study, we investigated the necessity and limitations of music composition required in TV documentary by conducting in-depth interviews with 20 music directors currently working at Korean Broadcasting System (KBS). Our research has shown that composition of music is necessary. However, in reality, it is difficult to use the composed music due to problems such as time and cost of composing and trust in the music composer; so music libraries, film music, or other music are used instead of the composed music in many situations. However, at the time when companies like its rival Netflix are aware of the importance of sound, the impact of Netflix could lead to a decline in the quality of terrestrial TV, which could lead to a weakening of competitiveness. Recently, in the case of sound programs, the sales of secondary works are active due to "internet uploading using YouTube" or "exporting programs", but the sales have been hindered by restrictions on the use of copyrighted works. The music source of library is said to be the one whose copyright problem has been resolved. In this study, we show that the composed music is an ultimate alternative to TV documentaries, since the library music is sometimes suspended due to the situations of management companies.

A Study on the Management of Printed Music in University Libraries (대학도서관에서의 악보자료 관리에 관한 연구 - 대전.충남지역을 중심으로 -)

  • Hahn, Kyung-Shin
    • Journal of Korean Library and Information Science Society
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    • v.41 no.3
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    • pp.205-224
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    • 2010
  • The purpose of this study aims to present the base for the rational management of printed music as an important primary source of music materials. In this study, therefore, the selection and acquisition, organization, user services for the management of printed music are investigated. Then the present situation for management of printed music of university libraries in Daejeon and Chungnam are surveyed. Finally, the special issues to be considered in the management of printed music are presented.

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The Effect of Music Therapy on the Physiological and Psychological Status of Women College Students Based on Their Preference of Music (음악선호도에 따른 음악요법이 여대생의 생리적, 심리적 변수에 미치는 효과)

  • Jeong, Hyeon-Cheol
    • Korean Journal of Adult Nursing
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    • v.20 no.2
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    • pp.321-330
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    • 2008
  • Purpose: This study was intended to determine how the choice of music affects the physiological and psychological status of women college student during music therapy. Methods: A nonequivalent experimental group pretest-posttest design was used. 19 out of 54 subjects were assigned to listen to their favorite music and 17 to their unfavorite music for 20 minutes using MP3 players and headphones. Anxiety, blood pressure, pulse and blood glucose levels of the subjects were measured before treatment. The data was analyzed by Mann-Whitney and Wilcoxon signed rank test using the SPSS/WIN 10.0 program. Results: The result showed that systolic blood pressure, blood glucose and anxiety level decreased significantly in the favorite music group. however systolic blood pressure, pulse rate and anxiety level increased significantly in the unfavorite music group. The favorite music group showed a significantly higher level of satisfaction than the unfavorite music group. Conclusion: Choice of music affects the physiological and psychological status of an individual. Favorite music listening would enhance the effect of music therapy. Therefore, selection of music must be considered in light of the subject's preference and characteristics.

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Speech/Music Discrimination Using Spectrum Analysis and Neural Network (스펙트럼 분석과 신경망을 이용한 음성/음악 분류)

  • Keum, Ji-Soo;Lim, Sung-Kil;Lee, Hyon-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.5
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    • pp.207-213
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    • 2007
  • In this research, we propose an efficient Speech/Music discrimination method that uses spectrum analysis and neural network. The proposed method extracts the duration feature parameter(MSDF) from a spectral peak track by analyzing the spectrum, and it was used as a feature for Speech/Music discriminator combined with the MFSC. The neural network was used as a Speech/Music discriminator, and we have reformed various experiments to evaluate the proposed method according to the training pattern selection, size and neural network architecture. From the results of Speech/Music discrimination, we found performance improvement and stability according to the training pattern selection and model composition in comparison to previous method. The MSDF and MFSC are used as a feature parameter which is over 50 seconds of training pattern, a discrimination rate of 94.97% for speech and 92.38% for music. Finally, we have achieved performance improvement 1.25% for speech and 1.69% for music compares to the use of MFSC.

Music Exploring Interface using Emotional Model (감성모델을 이용한 음악 탐색 인터페이스)

  • Yoo, Min-Joon;Kim, Hyun-Ju;Lee, In-Kwon
    • 한국HCI학회:학술대회논문집
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    • pp.707-710
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    • 2009
  • In this paper, we introduce an interface for exploring music using emotional model. First, we survey arousal-valence factors of various music and calculate a correlation between audio fefatures of music and arousal-valence factors to build an AV model. Then, various music is aligned and arranged using the AV model and the user can explore music in this interface. To select the desired music more intuitively, we introduce new fade in/out function based on the location of the user's mouse point. We also offer several mode of selecting music so user can explore music using most suitable mode of interface. With our interface, the user can find the emotionally desired music more easily.

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A Selection of Optimal EEG Channel for Emotion Analysis According to Music Listening using Stochastic Variables (확률변수를 이용한 음악에 따른 감정분석에의 최적 EEG 채널 선택)

  • Byun, Sung-Woo;Lee, So-Min;Lee, Seok-Pil
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.11
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    • pp.1598-1603
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    • 2013
  • Recently, researches on analyzing relationship between the state of emotion and musical stimuli are increasing. In many previous works, data sets from all extracted channels are used for pattern classification. But these methods have problems in computational complexity and inaccuracy. This paper proposes a selection of optimal EEG channel to reflect the state of emotion efficiently according to music listening by analyzing stochastic feature vectors. This makes EEG pattern classification relatively simple by reducing the number of dataset to process.

SYMMER: A Systematic Approach to Multiple Musical Emotion Recognition

  • Lee, Jae-Sung;Jo, Jin-Hyuk;Lee, Jae-Joon;Kim, Dae-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.2
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    • pp.124-128
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    • 2011
  • Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

Noise Source Localization by Applying MUSIC with Wavelet Transformation (웨이블렛 변환과 MUSIC 기법을 이용한 소음원 추적)

  • Cho, Tae-Hwan;Ko, Byeong-Sik;Lim, Jong-Myung
    • Transactions of the Korean Society of Automotive Engineers
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    • v.16 no.2
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    • pp.18-28
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    • 2008
  • In inverse acoustic problem with nearfield sources, it is important to separate multiple acoustic sources and to measure the position of each target. This paper proposes a new algorithm by applying MUSIC(Multiple Signal Classification) to the outputs of discrete wavelet transformation with sub-band selection based on the entropy threshold, Some numerical experiments show that the proposed method can estimate the more precise positions than a conventional MUSIC algorithm under moderately correlated signal and relatively low signal-to-noise ratio case.