• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.165-171
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• 2024

The processes of society's informatization and digitalization necessitate the widespread use of new pedagogical technologies. Through these technologies, comprehensive disclosure of didactic functions of new methods of educational activity and the realization of the potential and creative potential. The use of information and computer multimedia technologies in teaching music art is especially relevant in the intensification of the development of interactive technologies, the transition to mixed forms of learning, and a period of socio-economic and sociopolitical upheavals. The study aims to substantiate the theoretical and applied principles of the analysis of multimedia technology learning musical art in modern conditions and assess the status and trends in their use in conducting educational activities. The study uses general scientific and unique methods of economic analysis, in particular, analysis and synthesis, analogy and comparison, generalization and systematization, and graphic ways. Regarding the results of the study of multimedia technologies for teaching musical art in current conditions, it was found that they contribute to the development of the seeker's creative, creative, and cognitive activity, have a positive impact on learning material, and diversify the educational process. Multimedia technologies such as presentations, programs for watching a video, listening to audio, music and singing karaoke, electronic encyclopedias, and Internet resources are proven to be the most used in music education. They have several qualitative and quantitative advantages, manifested in the possibilities of audio-visual presentation of educational material and significantly higher information density. It is suggested to strengthen the use of such computer programs as Microsoft Word, Ahead Nero, Finale, Adobe Audition, Sound Forge, and Microsoft PowerPoint for musical art classes.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.650-657
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• 2006

The music is a part of our daily life in these days. And when the people listen to the music, they are affected by the context. However, previous researches on the music recommendation system have the problem that they didn't consider the proper contextual information efficiently. They only used the content-based filtering or the method to use musical metadata (genre, artist, etc.). Recently, there are some researches about the music recommendation system which applies the status(temperature, humidity, etc.) of environments. But, it is difficult to be accepted by the contextual information. Therefore, we propose the music recommendation system that is dynamically applied by the contextual information as well as the metadata in the previous researches. And the system can provide users with the music that they want to listen to, and then the users can be more satisfied. Also, the services can be improved by the feedback of the users. In order to solve this problem, the context-information for selecting a music list is defined and the music recommendation system is designed by using the content-based filtering method. The system is suitable for the user's taste and the context. The music recommendation system we are proposing uses an OSGi framework in the home network. As a result, the satisfaction of users and the quality of services will be improved more efficiently by supporting the mobility of services as well as the distributed processing.

• Speech Sciences
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• v.15 no.1
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• pp.75-83
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• 2008

The interior of an automobile is a very noisy environment with both stationary cruising noise and the reverberated music or speech coming out from the audio system. For robust speech recognition in a car environment, it is necessary to extract a driver's voice command well by removing those background noises. Since we can handle the music and speech signals from an audio system in a car, the reverberated music and speech sounds can be removed using an acoustic echo canceller. In this paper, we implement an acoustic echo canceller with robust double-talk detection algorithm using TMS-320C6711 DSK. First we developed the echo canceller on the PC for verifying the performance of echo cancellation, then implemented it on the TMS320C6711 DSK. For processing of one speech sample with 8kHz sampling rate and 256 filter taps of the echo canceller, the implemented system used only 0.035ms and achieved the ERLE of 20.73dB.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.161-165
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• 2011

Recently, According to increasing interest to original sound Karaoke instrument, MIDI type karaoke manufacturer attempt to make more cheap method instead of original recoding method. Separating technique for singing voice from music accompaniment is very useful in such equipment. We propose a system to separate singing voice from music accompaniment for stereo recordings. Our system consists of three stages. The first stage is a spectral change detector. The second stage classifies an input into vocal and non vocal portions by using GMM classifier. The last stage is a selective frequency separation stage. The results of removed by listening test from the results for computer based extraction simulation, spectrogram results show separation task successfully. Listening test with extracted MR from proposed system show vocal separating and removal task successfully.

• Speech Sciences
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• v.14 no.4
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• pp.169-178
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• 2007

This thesis describes the development of a service system for small-sized shops which support not only music broadcasting, but editing and generating voice announcement using the TTS(Text-To-Speech) technology. The system has been developed based on web environments with an easy access whenever and wherever it is needed. The system is able to control the sound using silverlight media player based on the ASP .NET 2.0 technology without any additional application software. Use of the Ajax control allows for multiple users to get the maximum load when needed. TTS is built in the server side so that the service can be provided without user's computer. Due to convenience and usefulness of the system, the business sector can provide better service to many shops. Further additional functions such as statistical analysis will undoubtedly help shop management provide desirable services.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.427-430
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• 1992

In this paper, we proposed an algorithm for the musical note recognition. Firstly, a given bit-mapped music score image is converted to a set of individual note pattern images via vertical projection. Then, the pitch of a note is determinal by comparison in the note-head position with the reference five-lines. Also, the length of a note is found via leader clustering with a set of normalized note patterns. Finally, a datafile to play the music is obtained using the pitch and length of musical notes. Experimental results with a simple musical score image show that the proposed scheme is performed well.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.65-70
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• 2020

For a wireless communication system, the angle-of-arrival (AOA) of the signal has a variety of applications. The signal AOA is estimated utilizing various antenna array structure such as Uniform Linear Array (ULA), Uniform Rectangular Array (URA), and Uniform Circular Array (UCA). In this paper, we introduce a cascade AOA estimation algorithm based on the UCA, which is consisted of CAPON and Beamspace MUSIC. CAPON is employed to estimate approximate AOA groups including multiple AOA signals and Beamspace MUSIC is employed to estimate detailed signal AOAs in the estimated AOA groups. In addition, we provide the computer simulation results for verifying and analyzing the performance of the cascade AOA estimator based on UCA.

• ETRI Journal
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• v.43 no.6
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• pp.1081-1092
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• 2021

Electroencephalography (EEG) recordings taken during the perception of music tempo contain information that estimates the tempo of a music piece. If information about this tempo stimulus in EEG recordings can be extracted and classified, it can be effectively used to construct a music-based brain-computer interface. This study proposes a novel convolutional recurrent attention model (CRAM) to extract and classify features corresponding to tempo stimuli from EEG recordings of listeners who listened with concentration to the tempo of musics. The proposed CRAM is composed of six modules, namely, network inputs, two-dimensional convolutional bidirectional gated recurrent unit-based sample encoder, sample-level intuitive attention, segment encoder, segment-level intuitive attention, and softmax layer, to effectively model spatiotemporal features and improve the classification accuracy of tempo stimuli. To evaluate the proposed method's performance, we conducted experiments on two benchmark datasets. The proposed method achieves promising results, outperforming recent methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1130-1141
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• 2015

Conventionally, a pulse radar is used for middle-sized or large-sized ships to detect other ships or obstacles located at a long distance. However, it is hardly equipped for most of the small-sized ships due to mounting and maintenance costs. Therefore, FMCW(frequency modulated continuous wave) radar is suggested as an alternative for the small-sized ships. Since it operates with low power and has good range resolution for relatively close objects, it is eligible for the small-sized ships. In previously proposed FMCW radar system, it only estimates distance and velocity of a target ship placed in the direction of main beam and is hard to detect several ships simultaneously. Thus, we suggest the method for detecting several ships at the same time by applying MUSIC(multiple signal classification) algorithm to FMCW radar signal received by a phased array antenna. In addition, by combining digital beam forming with the MUSIC algorithm, better angle resolution is achievable.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.97-104
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• 2007

This paper presents the problem of the feature extraction techniques that has been used a content-based analysis, classification and retrieval in audio data and proposes a course of the preprocessing for a new contents-based retrieval methods. Because the feature vector according to sampling value changes, the existing audio data analysis is problem that same music is appraised by other music. Therefore, we propose waveform information extraction method of PCM data for retrieval audio data of various format to contents-based. If this method is used. we can find that audio datas that get into sampling in various format are same data. And it may be applied in contents-based music retrieval system. To verity the performance of the method, an experiment was done feature extraction using STFT and waveform information extraction using PCM data. As a result, we could know that the method to propose is effective more.