• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.10 no.3
• /
• pp.215-220
• /
• 2016

Music braille is made up of more systematic and various symbols compared with text braille. Therefore, the translation of braille music requires extensive knowledge of the music and the braille symbols. Because currently the computer program for the text braille has already developed, we don't need any help from the braille translator. However, the translation of music braille is hard without the help of a professional music braille translator, because the translation computer program is not perfect. The current situation is that the music braille translator reads the music score and translates it into the braille himself. In this paper, we designed and implemented the "Braille Music Converter", you can implement a person does not understand the braille translation into music braille well. It includes translation into text braille for the lyrics processing and rest, octave, key signature, time signature, tie, slur, repeat mark was confirmed that the successful conversion to the actual music score.

• Phonetics and Speech Sciences
• /
• v.10 no.3
• /
• pp.19-29
• /
• 2018

We propose to use independent component analysis (ICA) and deep neural network (DNN) to detect music sections in broadcast drama contents. Drama contents mainly comprise silence, noise, speech, music, and mixed (speech+music) sections. The silence section is detected by signal activity detection. To detect the music section, we train noise, speech, music, and mixed models with DNN. In computer experiments, we used the MUSAN corpus for training the acoustic model, and conducted an experiment using 3 hours' worth of Korean drama contents. As the mixed section includes music signals, it was regarded as a music section. The segmentation error rate (SER) of music section detection was observed to be 19.0%. In addition, when stereo mixed signals were separated into music signals using ICA, the SER was reduced to 11.8%.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.22 no.5
• /
• pp.10-16
• /
• 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.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.7
• /
• pp.83-91
• /
• 2017

In this paper, we propose a thorough solution for adjusting virtual sound field with different kinds of devices and software in preliminary procedure and late stage of music processing. The basic process of music production includes composing, arranging and recording at pre-production stage as well as sound mixing and mastering at post-production stage. At the initial stage of music creation, it should be checked whether the design of virtual sound field, the choice of the tone and the instrument used in the arrangement match the virtual sound field required for the final work. In later recording, mixing and mastering, elaborate adjustments should be done to the virtual sound field. This study also analyzed how to apply the parameter of the effectors to the design and adjustment of the virtual sound field, making it the source of our creation.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.7
• /
• pp.93-100
• /
• 2017

In this paper, we propose a methodology of using time-lag, make it serve the sound field, in order to smoothen the music production and reduce conflicts. The importance of music production in today's music industry chain is becoming more and more apparent. In the process of music production, the creators pay more attention to the design and adjustment of virtual sound field, especially the late mixing and production. In the process, as a commonly used tool for the adjustment of sound field, "time-lapse" plays a decisive role.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.1
• /
• pp.417-420
• /
• 2005

This report shows the new music player's system which could separate music's tempo by analysis Peak level frequency by time from some percussion instruments. After this process, the new music player could classify some fast or slow genre's musics without a user's order, then we should listen to a fast or slow genre's music by a button.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.693-694
• /
• 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.

• Journal of Multimedia Information System
• /
• v.4 no.3
• /
• pp.99-106
• /
• 2017

This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.243-244
• /
• 2006

In this study, we propose a speech/music discrimination method using spectral peak track analysis. The proposed method uses the spectral peak track's duration at the same frequency channel for feature parameter. And use the duration threshold to discriminate the speech/music. Experiment result, correct discrimination ratio varies according to threshold, but achieved a performance comparable to another method and has a computational efficient for discrimination.

• Science of Emotion and Sensibility
• /
• v.16 no.3
• /
• pp.363-372
• /
• 2013

When retrieving music with folksonomy tags, internal use of numeric tags (AV tags: tags consisting of Arousal and Valence values ) instead of word tags can partially solve the problem posed by synonyms. However, the two predecessor tasks should be done correctly; the first task is to map word tags to their numeric tags; the second is to get numeric tags of the music pieces to be retrieved. The first task is verified through our prior study and thus, in this paper, its significance is seen for the second task. To this end, we propose the music mapping table defining the relation between AV values and music and ANOVA tests are performed for analysis. The result shows that the arousal values and valence values of music have different distributions for 12 mood tags with or without synonymy and that their type I error values are P<0.001. Consequently, it is checked that the distribution of AV values is different according to music mood.