Music Information Systems Research Articles

ANALISA HUKUM ATAS KEPEMILIKAN SAH BAGI HAK CIPTA LAGU ATAU MUSIK (PERATURAN NOMOR 56 TAHUN 2021)

The uncertainty of legal regulations concerning the economic entitlements of songwriters or musicians and related rights in asserting royalties can arise due to the failure to register the data of songwriters or musicians along with their related rights in the Song and Music Information System (SILM) and the Directorate General of Intellectual Property (DJKI) database. In an attempt to offer legal safeguard for copyright or related rights in the music industry that are not registered in SILM, this study seeks to examine the legal consequences of such situations and the patterns of dispute resolution. Through observation of the research object and the degree of its application in practice, empirical sociology is the applied method used to evaluate the efficiency of legal tools in complying with prevailing regulations. Findings indicate that in cases of music compositions or songs not included in SILM, users are willing to pay royalties in exchange for not releasing new recordings, and that to achieve mutually beneficial agreements, conflict resolution procedures typically require mediation through PPNS before resorting to litigation.

The Legal Certainty of Legitimate Ownership in Copyright Works of Songs or Music, as well as Associated Rights in Non-Declarative Recording in accordance with the Royalty Management System under Government Regulation No. 56 of 2021 (Case Study on Copyrigh

The non-registration of data on song or music creators and related rights in the Directorate General of Intellectual Property (DJKI) database and the Song and Music Information System (SILM) could lead to legal uncertainty regarding the economic rights of song or music creators and related rights in claiming royalty rights. This research aims to explore the legal consequences of a song or music copyright/related rights that are not registered in the SILM and the dispute resolution patterns as efforts to provide legal protection for unregistered song or music copyrights/related rights in the SILM. The applied method is empirical sociology to assess the effectiveness of legal instruments in accordance with applicable regulations by observing the research objects and the level of their implementation in practice. The results indicate that for works of music or songs not recorded in the SILM, royalty payments are made voluntarily by users with the condition of not creating new records, and dispute resolution patterns involve mediation through the PPNS before proceeding to litigation to seek a win-win solution.

Theoretical Study Of Legal Protection Of Song Royalty On Digital Platforms

<p><em>The purpose of this study is to solve problems related to legal arrangements regarding song royalties or music on digital platforms that are used commercially and the issue of violations of song royalties on digital platforms today. This type of research is normative legal research with primary legal materials covering the applicable laws and regulations and secondary legal materials, including law books, the internet, and journals related to the issues studied.</em> <em>This research is descriptive, while the research material is carried out qualitatively. This research results in a conclusion that the matter of collecting royalties for songs on the Digital Platform after the issuance of Government Regulation of the Republic of Indonesia Number 56 of 2021 concerning Management of Royalties for Copyright of Songs and/or Music only targets the form of public services but does not regulate strictly in the form of Digital services that are used commercially and Legal protection regarding royalties for songs or music in Digital Platforms that are used commercially is divided into 2 (two), namely: Legal protection in the form of protection of works and rights for songwriters in the form of economic rights and moral rights, legal protection in the form of criminal sanctions and civil sanctions in the form of compensation. The responsibility of Government must immediately make derivative regulations relating to the Management of Song Royalties in Digital Platforms that are used commercially to provide protection and legal certainty for those who have economic rights/song royalties, as well as the Directorate General of Intellectual Property (DJKI) to be able to complete the Song / Music Information System (SILM) song and music data center to optimize the withdrawal and distribution of royalties to songwriters or musicians.</em><em></em></p>

University students’ use of music for learning and well-being: A qualitative study and design implications

Music has long been recognised to be able to alter people's emotions and behaviours, yet how university students use music for learning and well-being is largely unexplored. With one of the largest music user populations in the world, China has tremendous market potential for digital music. This study explores music use behaviours for learning and well-being among university students in China and how these findings can inform future online music service design. An investigation framework is developed based on theories in multiple related disciplines such as musicology, psychology, and sociology. In-depth interviews were conducted with forty university students in twenty universities, with an interview protocol designed based on the framework. Interview transcriptions were analysed using a thematic content analysis approach. The results reveal how students use music for multiple aspects of life corresponding to learning and major components of well-being, including physical well-being, social relationships, positive emotion, self-esteem, and meaning of life. Based on the findings we discuss emerging themes on the design of online music information systems and services. This study fills the research gap on how music is used by university students for benefiting learning and well-being. The design implications are valuable for online music services to better meet users’ evolving needs. The proposed framework and method can be readily used to study music users in various populations.

Turkish Music Genre Classification using Audio and Lyrics Features

Music Information Retrieval (MIR) has become a popular research area in recent years. In this context, researchers have developed music information systems to find solutions for such major problems as automatic playlist creation, hit song detection, and music genre or mood classification. Meta-data information, lyrics, or melodic content of music are used as feature resource in previous works. However, lyrics do not often used in MIR systems and the number of works in this field is not enough especially for Turkish. In this paper, firstly, we have extended our previously created Turkish MIR (TMIR) dataset, which comprises of Turkish lyrics, by including the audio file of each song. Secondly, we have investigated the effect of using audio and textual features together or separately on automatic Music Genre Classification (MGC). We have extracted textual features from lyrics using different feature extraction models such as word2vec and traditional Bag of Words. We have conducted our experiments on Support Vector Machine (SVM) algorithm and analysed the impact of feature selection and different feature groups on MGC. We have considered lyrics based MGC as a text classification task and also investigated the effect of term weighting method. Experimental results show that textual features can also be effective as well as audio features for Turkish MGC, especially when a supervised term weighting method is employed. We have achieved the highest success rate as 99,12\% by using both audio and textual features together.

THE INFLUENCE OF LISTENER PERSONALITY ON MUSIC CHOICES

To deliver better recommendations, music information systems need to go beyond standard methods for musical taste prediction. Tracking the listener’s emotions is one way to improve the quality of recommendations. This can be achieved explicitly, by asking the listener to report his/her emotional state, or implicitly, by tracking the context in which the music is heard. However, the factors that induce particular emotions vary among individuals. This paper presents initial research on the influence of an individual’s personality on his or her choice of music. The psychological profile of a group of 16 students was determined by a questionnaire. The participants were asked to label their own music collections, listen to the music, and mark their emotions using a custom application. Statistical analysis revealed correlations between low-level audio features, personality types, and emotional states of the students.

A Conceptualization of Music Sound Recordings and Its Representation in an Ontology

Music is a domain with several dimensions and some specific characteristics. When different types of music are considered, modeling this domain becomes even more challenging. This paper presents some of the characteristics that makes music such an interesting domain to model and summarizes a conceptualization process based on the Dahlberg conceptual triangle for guiding the construction of an ontology proposal for representing music sound recordings. This ontology can provide a global representation that might be used to support music information systems’ interoperability as well as data integration, contributing to worldwide music dissemination in nowadays knowledge society. Some possible mappings to other representational schemes for music sound recordings are identified to enable interoperability and integration with other similar systems. An interview with domain specialists indicates the right coverage of the necessary concepts, and evidences the importance of the proposal.

Exploring the music similarity space on the web

This article comprehensively addresses the problem of similarity measurement between music artists via text-based features extracted from Web pages. To this end, we present a thorough evaluation of different term-weighting strategies, normalization methods, aggregation functions, and similarity measurement techniques. In large-scale genre classification experiments carried out on real-world artist collections, we analyze several thousand combinations of settings/parameters that influence the similarity calculation process, and investigate in which way they impact the quality of the similarity estimates. Accurate similarity measures for music are vital for many applications, such as automated playlist generation, music recommender systems, music information systems, or intelligent user interfaces to access music collections by means beyond text-based browsing. Therefore, by exhaustively analyzing the potential of text-based features derived from artist-related Web pages, this article constitutes an important contribution to context-based music information research.

A music information system automatically generated via Web content mining techniques

This article deals with the problem of mining music-related information from the Web and representing this information via a music information system. Novel techniques have been developed as well as existing ones refined in order to automatically gather information about music artists and bands. After searching, retrieval, and indexing of Web pages that are related to a music artist or band, Web content mining and music information retrieval techniques were applied to capture the following categories of information: similarities between music artists or bands, prototypicality of an artist or a band for a genre, descriptive properties of an artist or a band, band members and instrumentation, images of album cover artwork. Approaches to extracting these pieces of information are presented and evaluation experiments are described that investigate the proposed approaches’ performance. From the insights gained by the various experiments an Automatically Generated Music Information System (AGMIS) providing Web-based access to the extracted information has been developed. AGMIS demonstrates the feasibility of automated music information systems on a large collection of more than 600,000 music artists.

N-gram inverted index structures on music data for theme mining and content-based information retrieval

Content-based music information retrieval and theme mining are two key problems in digital music information systems, where “themes” mean the longest-repeating patterns in a piece of music. However, most data structures constructed for retrieving music data cannot be efficiently used to mine the themes of music pieces, and vice versa. The suffix tree structure can be used for both functions, nevertheless its size is too large and its maintenance is somewhat difficult. In this paper, a kind of index structure is introduced, which adopts the idea of inverted files and that of n-gram. It can be used to retrieve music data as well as to mine music themes. Based on the index and several useful concepts, a theme mining algorithm is proposed, and the theoretical analysis is also given. In addition, two implementations of a content-based music information retrieval algorithm are presented. Experiments show the correctness and efficiency of the proposed index and algorithms.

The Danish Music Information System: the design of a Web gateway to Danish music resources

The pre-project, Music Information Denmark [1], is initiated by The Danish National Library Authority and aims to simplify access to information about Danish music and Danish musical life. On the basis of user needs of the participating group of five public libraries together with the information on music from a number of institutions which possess an extensive electronically stocked knowledge of Danish music, MIC (the Danish Music Information Centre), the Royal Library, the State Media Archive, the Danish Broadcasting Corporation and the Danish LibraryCentre A/S, a Web gateway is designed containing information on Danish musicians. ensembles, works and sheet music, discographies and events. The project treats the problems of collecting. storing and digitization of music information - text, sound, images as well as copyright problems.