• Journal of the Korean Society for information Management
• /
• v.29 no.1
• /
• pp.175-190
• /
• 2012

This study aims to investigate the current status of mobile search functions of Korean search portals, namely Google Korea, Naver, Nate, Daum, and Yahoo Korea. This study focuses on unique mobile search functionalities, such as voice search, music search, code search, and visual/ object search. In particular, this study analyzed characteristics of these search functions and evaluated their performances based on the accuracy and the speed of recognition. The results of this study show that both Naver and Daum support various mobile searching functions, whereas Google only supports voice search. Nate and Yahoo do not offer any unique function. The results of this study can be applied to the portal's effective development of mobile search functionalities.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.2
• /
• pp.200-206
• /
• 2024

Computing music similarity is an indispensable component in developing music search service. This paper proposes a relevance weight of each chromagram vector for cover song identification in computing a music similarity function in order to boost identification accuracy. We derive a music similarity function using the relevance weight based on the probabilistic relevance model, where higher relevance weights are assigned to less frequently-occurring discriminant chromagram vectors while lower weights to more frequently-occurring ones. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.

• Journal of the Korean Society for information Management
• /
• v.30 no.3
• /
• pp.23-48
• /
• 2013

This study compared and analyzed 15 CBMR (Content-based Music Retrieval) systems accessible on the web in terms of DB size and type, query type, access point, input and output type, and search functions, with reviewing features of music information and techniques used for transforming or transcribing of music sources, extracting and segmenting melodies, extracting and indexing features of music, and matching algorithms for CBMR systems. Application of text information retrieval techniques such as inverted indexing, N-gram indexing, Boolean search, truncation, keyword and phrase search, normalization, filtering, browsing, exact matching, similarity measure using edit distance, sorting, etc. to enhancing the CBMR; effort for increasing DB size and usability; and problems in extracting melodies, deleting stop notes in queries, and using solfege as pitch information were found as the results of analysis.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.27-32
• /
• 2024

Reliable and fine-grained musical metadata are required for efficient search of rapidly increasing music files. In particular, since the primary motive for listening to music is its emotional effect, diversion, and the memories it awakens, emotion classification along with genre classification of music is crucial. In this paper, as an initial approach towards a "ground-truth" dataset for music emotion and genre classification, we elaborately generated a music corpus through labeling of a large number of ordinary people. In order to verify the suitability of the dataset through the classification results, we extracted features according to MPEG-7 audio standard and applied different machine learning models based on statistics and deep neural network to automatically classify the dataset. By using standard hyperparameter setting, we reached an accuracy of 93% for genre classification and 80% for emotion classification, and believe that our dataset can be used as a meaningful comparative dataset in this research field.

• Journal of Intelligence and Information Systems
• /
• v.12 no.2
• /
• pp.1-15
• /
• 2006

Currently the mobile web service is growing with a tremendous speed and mobile contents are spreading extensively. However, it is hard to search what the user wants because of some limitations of cellular phones. And the music is the most popular content, but many users experience frustrations to search their desired music. To solve these problems, this research proposes a hybrid recommendation system, MOBICORS-music (MOBIle COntents Recommender System for Music). Basically it follows the procedure of Collaborative Filtering (CF) system, but it uses Contents-Based (CB) data representation for neighborhood formation and recommendation of new music. Based on this data representation, MOBICORS-music solves the new item ramp-up problem and results better performance than existing CF systems. The procedure of MOBICORS-music is explained step by step with an illustrative example.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.4
• /
• pp.275-280
• /
• 2015

In this paper, we studied for modified MUSIC algorithm of direction of arrival (DOA)estimation. Modified MUSIC algorithm search optimal covariance matrix using singular value decomposition and Bayes method, and desired signals are estimated by updating weight. In order to estimation of desired signals, we used sub spatial method of MUSIC algorithm. General MUSIC algorithm can estimate a desired signal in case of non-correlation signal. But, general MUSIC algorithm in case of correlation signal can not estimate a desired signals and resolution is decreased. Though simulation in case of correlation signal, we analyze to compare proposed MUSIC algorithm with general MUSIC algorithm.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.725-732
• /
• 2009

Thanks to the development of the Internet, people can easily access a vast amount of music. This brings attention to application systems such as a melody-based music search service or music recommendation service. Extracting melodies from music is a crucial process to provide such services. This paper introduces a novel algorithm that can extract melodies from piano music. Since piano can produce polyphonic music, we expect that by studying melody extraction from piano music, we can help extract melodies from general polyphonic music.

• Journal of Korea Multimedia Society
• /
• v.22 no.6
• /
• pp.639-645
• /
• 2019

This paper proposes a salient chromagram components extraction method based on the temporal discrete cosine transform of a chromagram block to improve cover song retrieval accuracy. The proposed salient chromagram emphasizes tonal contents of music, which are well-preserved between an original song and its cover version, while reducing the effects of timbre difference. We apply the proposed salient chromagram extraction method as a preprocessing step for the Fourier-transform based cover song matching. Experiments on two cover song datasets confirm that the proposed salient chromagram improves the cover song search accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37C no.11
• /
• pp.1077-1083
• /
• 2012

The jamming countermeasures in GNSS includes anti-jamming technique and jammer localization technique. In both techniques, direction of jamming signal is important and generally the MUSIC algorithm is used to find the direction of jamming signal. The MUSIC is super-resolution algorithm for detecting incident direction of signal. But, the search time of MUSIC algorithm is too long because all candidates of incidence angle are searched. This paper proposes the new method that has less computational burdens and therefore faster than the conventional MUSIC algorithm. The proposed method improves performance speed by reducing unnecessary calculations. In the proposed method, the cost function of conventional MUSIC algorithm is decomposed into the sum of squares and if the partial sum of cost function is larger than the minimum cost function so far, then the candidate is rejected and next candidates are searched. If the computed cost function is less than the minimum cost function so far, the minimum cost function so far is replaced with newly computed value. The performance of the proposed method was compared with the conventional MUSIC algorithm using the simulation. The accuracy of the estimaed direction of jamming signal was same as the conventional MUSIC while the search speed of the proposed method was 1.15 times faster than the conventional MUSIC.

• Journal of the Korean Society for Library and Information Science
• /
• v.44 no.4
• /
• pp.395-412
• /
• 2010

This study aims to perform an evaluation of multimedia search services provided by major Korean search portals: Naver, Nate, Daum, Yahoo-Korea, Paran, and Google-Korea. These multimedia search services are evaluated in terms of the metadata of search results, search functionalities, searching methods, other functionalities, and display options. Every search portal offers image and video searching, whereas only Naver, Nate, and Daum offer music searching. Advanced searching methods and functions are mostly developed and supported in image and video searching rath than music searching. Naver, Nate, and Daum support various searching functions which search portals abroad have not developed. Google-Korea supports advanced searching functions. Search portals provide a limited number of metadata in search results. This study could contribute to the development and improvement of portal's multimedia search services.