• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.141-149
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• 2003

As music of digital form has been widely used, many people have been interested in the automatic extraction of natural information of music itself, such as key of a music, chord progression, melody progression, tempo, etc. Although some studies have been tried, consistent and reliable results of musical information extraction had not been achieved. In this paper, we propose a method to extract chord and tempo information from general polyphonic music signals. Chord can be expressed by combination of some musical notes and those notes also consist of some frequency components individually. Thus, it is necessary to analyze the frequency components included in musical signal for the extraction of chord information. In this study, we utilize a sinusoidal modeling, which uses sinusoids corresponding to frequencies of musical tones, and show reliable chord extraction results of sinusoidal modeling. We could also find that the tempo of music, which is the one of remarkable feature of music signal, interactively supports the chord extraction idea, if used together. The proposed scheme of musical feature extraction is able to be used in many application fields, such as digital music services using queries of musical features, the operation of music database, and music players mounting chord displaying function, etc.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.692-700
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• 2008

In some previous works on musical genre classification, human experts specify segments of a song for extracting musical features. Although this approach might contribute to performance enhancement, it requires manual intervention and thus can not be easily applied to new incoming songs. To extract musical features without the manual intervention, most of recent researches on music genre classification extract features from a pre-determined part of a song (for example, 30 seconds after initial 30 seconds), which may cause loss of accuracy. In this paper, in order to alleviate the accuracy problem, we propose a new method, which extracts features from representative segments (or main theme part) identified by structure analysis of music piece. The proposed method detects segments with repeated melody in a song and selects representative ones among them by considering their positions and energies. Experimental results show that the proposed method significantly improve the accuracy compared to the approach using a pre-determined part.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.263-273
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• 2020

In 2019, Disney's musical film "Aladdin" was newly introduced with Princess Jasmine's theme song "Speechless," which was not featured in the animation "Aladdin" in 1992. Written as a theme song, "Speechless" expresses Princess Jasmine as a self-reliant, enterprising and dignified woman. The song made the change in Princess Jasmine's character very articulate. She has developed herself as an active and enthusiastic character from a rather passive and reserved figure. The musical film "Aladdin" has drawn much attention and love from many audiences with its own narrative and original songs, but the addition of a new theme song "Speechless", which was not in the animation in 1992, made the musical film "Aladdin" even more powerful and meaningful. The study examined the organic relationship between the musical features and narratives of the newly included theme song 'Speechless' in the musical film Aladdin. Through the analysis of the six scenes that include the musical features of the theme song "Speechless," the study looked at how the relationship between music and narratives had an influence on cinematic expression.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.13-23
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• 2024

Music brings pleasure and relaxation to people. Therefore, it is necessary to classify musical genres based on scenes. Identifying favorite musical genres from massive music data is a time-consuming and laborious task. Recent studies have suggested that machine learning algorithms are effective in distinguishing between various musical genres. However, meeting the actual requirements in terms of accuracy or timeliness is challenging. In this study, a hybrid machine learning model that combines a deep residual auto-encoder (DRAE) and support vector machine (SVM) for musical genre recognition was proposed. Eight manually extracted features from the Mel-frequency cepstral coefficients (MFCC) were employed in the preprocessing stage as the hybrid music data source. During the training stage, DRAE was employed to extract feature maps, which were then used as input for the SVM classifier. The experimental results indicated that this method achieved a 91.54% F1-score and 91.58% top-1 accuracy, outperforming existing approaches. This novel approach leverages deep architecture and conventional machine learning algorithms and provides a new horizon for musical genre classification tasks.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.549-559
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• 2016

Currently the terminology 'rock musical' is used too freely, and thus academic definition and research of its stylistic features are required. This thesis attempts to clarify the historical context of rock music and rock muscal, and to study the musical and dramatic feature of rock musical. This thesis also attempts to catagolize the musical types of the songs used in the contemporary rock musial ; 1) authentic rock music, 2) psudo-rock music transformed from other musical styles, and 3) amalgamation of rock music and other musical styles. All this attempts is aimed to find a possibility of creation of new musical.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.265-269
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• 2010

This paper proposes a novel spectral audio feature, spectral contrast MFCC (SCMFCC), and studies its performance on the musical genre classification. For a successful musical genre classifier, extracting features that allow direct access to the relevant genre-specific information is crucial. In this regard, the features based on the spectral contrast, which represents the relative distribution of the harmonic and non-harmonic components, have received increased attention. The proposed SCMFCC feature utilizes the spectral contrst on the mel-frequency cepstrum and thus conforms the conventional MFCC in a way more relevant for musical genre classification. By performing classification test on the widely used music DB, we compare the performance of the proposed feature with that of the previous ones.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.724-726
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• 1999

We have developed a real time musical visualizing system works on PC with sound card and windows 95 or more. The system can extract some features of music signal and animate various screen -i.e wave, spectrum, simulated water jet - according to extracted features. We have used the system at the concert for the deaf and contributed for deaf to understand the music.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1502-1508
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• 2017

A musical key is a fundamental concept in Western music theory. It is a collective characterization of pitches and chords that together create a musical perception of the entire piece. It is based on a group of pitches in a scale with which a music is constructed. Each key specifies the set of seven primary chromatic notes that are used out of the twelve possible notes. This paper presents a method that identifies the key of a song using Hidden Markov Models given a sequence of chroma features. Given an input song, a sequence of chroma features are computed. It is then classified into one of the 24 keys using a discrete Hidden Markov Models. The proposed method can help musicians and disc-jockeys in mixing a segment of tracks to create a medley. When tested on 120 songs, the success rate of the music key identification reached around 87.5%.

• Speech Sciences
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• v.10 no.3
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• pp.133-144
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• 2003

The purpose of this acoustic experimental study was to investigate interrelation between prosodic features of Korean spoken language and those of Korean folk songs. The words of Changbutaryoung were spoken for analysis of spoken language by three female graduate students and the song was sung for musical features by three Kyunggi Minyo singers. Pitch contours were analyzed from sound spectrogram made by Pitch Works. Results showed that special musical voices (breaking, tinkling, vibrating, etc.) and tunes (rising, falling, level, etc) of folk song were discovered at the same place where accents of spoken language came. It appeared that, even though the patterns of pitch contour were different from each other, there was positive interrelation between prosodic features of Korean spoken language and those of Korean folk songs.

• Journal of the Korean Society of Costume
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• v.64 no.7
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• pp.114-127
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• 2014

Performing arts offer fun and knowledge and are directed for various purposes. Performing arts are also used as a means for education. Children's English media musical, 'The Magic Flute' is the performance reflecting all these. The author of this study took part in stage costume production, and this study was carried out aiming at designing and producing stage costume in line with educational purpose and intention. This study consists of an analysis stage for the existing performances of 'The Magic Flute', and a stage costume design and production stage for children's English media musical, 'The Magic Flute', First, this study classified and analyzed the stage design and stage costume design of the existing 'The Magic Flute' by concept, and then, examined their features, respectively. and this study unfolded the stage costume concept, based on the analyses of existing performance's stage costume and the characters' personality and features described in the current study subject's script. As the last step of this study made each character's stage costume. A total of 69 costumes for stage costume were made for 7 types of characters. This study is considered to have huge significance in that the stage costume was developed for 'The Magic Flute'.