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2006, Dagstuhl Seminar Proceedings
Abstract. Search and retrieval of specific musical content such as emotive or sonic features has become an important aspect of Music Information Retrieval system development, but only little research is user-oriented. We summarize results of an elaborate user-study that explores ...
This paper presents an overview of user studies in the Music Information Retrieval (MIR) literature. A focus on the user has repeatedly been identified as a key requirement for future MIR research; yet empirical user studies have been relatively sparse in the literature, the overwhelming research attention in MIR remaining systems-focused. We present research topics, methodologies, and design implications covered in the user studies conducted thus far.
Journal of Intelligent Information System, 2013
Most Music Information Retrieval (MIR) researchers will agree that understanding users' needs and behaviors is critical for developing a good MIR system. The number of user studies in the MIR domain has been gradually increasing since the early 2000s, reflecting this growing appreciation of the need for empirical studies of users. However, despite the growing number of user studies and the wide recognition of their importance, it is unclear how great their impact has been in the field: on how systems are developed, how evaluation tasks are created, and how MIR system developers in particular understand critical concepts such as music similarity or music mood. In this paper, we present our analysis on the growth, publication and citation patterns, topics, and design of 198 user studies. This is followed by a discussion of a number of issues/challenges in conducting MIR user studies and distributing the research results.
Journal of Intelligent Information Systems, 2013
Personalization and context-awareness are highly important topics in research on Intelligent Information Systems. In the fields of Music Information Retrieval (MIR) and Music Recommendation in particular, user-centric algorithms should ideally provide music that perfectly fits each individual listener in each imaginable situation and for each of her information or entertainment needs. Even though preliminary steps towards such systems have recently been presented at the "International Society for Music Information Retrieval Conference" (ISMIR) and at similar venues, this vision is still far away from becoming a reality. In this article, we investigate and discuss literature on the topic of user-centric music retrieval and reflect on why the breakthrough in this field has not been achieved yet. Given the different expertises of the authors, we shed light on why this topic is a particularly challenging one, taking computer science and psychology points of view. Whereas the computer science aspect centers on the problems of user modeling, machine learning, J Intell Inf Syst and evaluation, the psychological discussion is mainly concerned with proper experimental design and interpretation of the results of an experiment. We further present our ideas on aspects crucial to consider when elaborating user-aware music retrieval systems.
2012
ABSTRACT Most Music Information Retrieval (MIR) researchers will agree that understanding users' needs and behaviors is critical for developing a good MIR system. The number of user studies in the MIR domain has been gradually increasing since the early 2000s reflecting the need for empirical studies of users.
2008
A large-scale study was set up aiming at the clarification of the influence of demographic and musical background on the semantic description of music. Our model for rating high-level music qualities distinguishes between affective/ emotive, structural and kinaesthetic descriptors. The focus was on the understanding of the most important attributes of music in view of the development of efficient search and retrieval systems. We emphasized who the users of such systems are and how they describe their favorite music. Particular interest went to inter-subjective similarities among listeners. The results from our study suggest that gender, age, musical expertise, active musicianship, broadness of taste and familiarity with the music have an influence on the semantic description of music.
Personalized and user-aware systems for retrieving multimedia items are becoming increasingly important as the amount of available multimedia data has been spiraling. A personalized system is one that incorporates information about the user into its data processing part (e.g., a particular user taste for a movie genre). A context-aware system, in contrast, takes into account dynamic aspects of the user context when processing the data (e.g., location and time where/when a user issues a query). Today's user-adaptive systems often incorporate both aspects. Particularly focusing on the music domain, this article gives an overview of different aspects we deem important to build personalized music retrieval systems. In this vein, we first give an overview of factors that influence the human perception of music. We then propose and discuss various requirements for a personalized, user-aware music retrieval system. Eventually, the state-of-the-art in building such systems is reviewed, ...
Archives of Acoustics, 2008
This paper presents the main issues related to music information retrieval (MIR) domain. MIR is a multi-discipline area. Within this domain, there exists a variety of approaches to musical instrument recognition, musical phrase classification, melody classification (e.g. queryby-humming systems), rhythm retrieval, high-level-based music retrieval such as looking for emotions in music or differences in expressiveness, music search based on listeners' preferences, etc. The key-issue lies, however, in the parameterization of a musical event. In this paper some aspects related to MIR are shortly reviewed in the context of possible and current applications to this domain.
ISMIR Proceedings, 2004
User studies focusing upon real-life music information needs, uses and seeking behaviours are still very scarce in the music information retrieval (MIR) and music digital library (MDL) fields. We are conducting a multigroup survey in an attempt to acquire information that can help eradicate false assumptions in designing MIR systems. Our goal is to provide an empirical basis for MIR/MDL system development. In this paper, we present our preliminary findings and analyses based on the 427 user responses we have received to date. Two major themes have been uncovered thus far that could have a significant influence the future development of successful MIR/MDL systems. First, people display "public information-seeking" behaviours by making use of collective knowledge and/or opinions of others about music such as reviews, ratings, recommendations, etc. in their music information-seeking. Second, respondents expressed needs for contextual metadata in addition to traditional bibliographic metadata.
Journal of the Association for Information Science and Technology, 2004
We have explored methods for music information retrieval for polyphonic music stored in the MIDI format. These methods use a query, expressed as a series of notes that are intended to represent a melody or theme, to identify similar pieces. Our work has shown that a three-phase architecture is appropriate for this task, in which the first phase is melody extraction, the second is standardisation, and the third is query-to-melody matching. We have investigated and systematically compared algorithms for each of these phases. To ensure that our results are robust, we have applied methodologies that are derived from text information retrieval: we developed test collections and compared different ways of acquiring test queries and relevance judgements. In this paper we review this program of work, compare to other approaches to music information retrieval, and identify outstanding issues.
Journal of the American Society for Information Science and Technology, 2004
This article describes the digital music library work at the University of Waikato, New Zealand. At the heart of the project is a music information retrieval workbench for evaluating algorithms and performing experiments used in conjunction with four datasets of symbolic notation ranging from contemporary to classical pieces. The outcome of this experimentation is woven together with strands from our larger digital library project to form the Web-based music digital library MELDEX (short for melody index). An overview of the workbench software architecture is given along with a description of how this fits the larger digital library design, followed by several examples of MELDEX in use.
Personalized and user-aware systems for retrieving multimedia items are becoming increasingly important as the amount of available multimedia data has been spiraling. A personalized system is one that incorporates information about the user into its data processing part (e.g., a particular user taste for a movie genre). A context-aware system, in contrast, takes into account dynamic aspects of the user context when processing the data (e.g., location and time where/when a user issues a query). Today's user-adaptive systems often incorporate both aspects.
2006
The maturing of music information retrieval (MIR) systems outlines an attractive future for emotion-based retrieval of music. The present paper reports the results of an elaborate study which explores (1) who potential users of MIR systems are, (2) how they perceive affects in music, and what structural descriptions of music best characterize their understanding of music expression. 79 potential users of music information retrieval systems rated sets of adjectives, while they were listening to 160 music excerpts. The stimuli reflect the musical taste of the average participant in a large survey on the demographic and music background of people who are interested in using interactive music systems. The subject group (79) in the annotation experiment was recruited amongst the 774 participants in the survey. The study reveals that perceived qualities of music are affected by the profile of the user. Significant subject dependencies are found for age, music expertise, musicianship, broadness of taste and familiarity with classical music. Interesting relationships are discovered between expressive and structural features. Analyses show that the targeted population most unanimously agrees on loudness and tempo, whilst less unanimity was found for timbre and articulation. A semantic music recommender system is presented that was developed for validating the experimental results in the real world. A test has demonstrated the potential of a user-dependent and emotionbased retrieval of music.
2006
Abstract Efficient and intelligent music information retrieval is a very important topic of the 21st century. With the ultimate goal of building personal music information retrieval systems, this paper studies the problem of intelligent music information retrieval. Huron points out that since the preeminent functions of music are social and psychological, the most useful characterization would be based on four types of information: genre, emotion, style, and similarity.
Journal of Intelligent Information Systems
Increasing availability of music data via Internet evokes demand for efficient search through music files. Users' interests include melody tracking, harmonic structure analysis, timbre identification, and so on. We visualize, in an illustrative example, why content based search is needed for music data and what difficulties must be overcame to build an intelligent music information retrieval system.
2016
Sample retrieval remains a central problem in the creative process of making electronic dance music. This paper describes the findings from a series of interview sessions involving users working creatively with electronic music. We conducted in-depth interviews with expert users on location at the Red Bull Music Academies in 2014 and 2015. When asked about their wishes and expectations for future technological developments in interfaces, most participants mentioned very practical requirements of storing and retrieving files. A central aspect of the desired systems is the need to provide increased flow and unbroken periods of concentration and creativity. From the interviews, it becomes clear that for Creative MIR, and in particular, for music interfaces for creative expression, traditional requirements and paradigms for music and audio retrieval differ to those from consumer-centered MIR tasks such as playlist generation and recommendation and that new paradigms need to be considered. Despite all technical aspects being controllable by the experts themselves, searching for sounds to use in composition remains a largely semantic process. From the outcomes of the interviews, we outline a series of possible conclusions and areas and pose two research challenges for future developments of sample retrieval interfaces in the creative domain. 1. MOTIVATION AND CONTEXT Considerable effort has been put into analysing user behaviour in the context of music retrieval in the past two decades [35]. This includes studies on music information seeking behaviour [14,17], organisation strategies [15], usage of commercial listening services [36], the needs or motivations of particular users, such as kids [28], adolescents [34], or musicologists [29], and behaviour analysis for specific tasks, e.g., playlist and mix generation [13], or in specific settings, e.g., riding together in a car [16] or in music lessons in secondary schools [49].
2002
Abstract The majority of existing work in music information retrieval for audio signals has followed the content-based query-by-example paradigm. In this paradigm a musical piece is used as a query and the result is a list of other musical pieces ranked by their content similarity. In this paper we describe algorithms and graphical user interfaces that enable novel alternative ways for querying and browsing large audio collections. Computer audition algorithms are used to extract content information from audio signals.
Proceedings of the second …, 2008
Signals and Communication Technology, 2017
2008
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In this study, the notion of perceptual features is introduced for describing general music properties based on human perception. This is an attempt at rethinking the concept of features, in order to understand the underlying human perception mechanisms. Instead of using concepts from music theory such as tones, pitches, and chords, a set of nine features describing overall properties of the music was selected. They were chosen from qualitative measures used in psychology studies and motivated from an ecological approach. The selected perceptual features were rated in two listening experiments using two different data sets. They were modeled both from symbolic (MIDI) and audio data using different sets of computational features. Ratings of emotional expression were predicted using the perceptual features. The results indicate that (1) at least some of the perceptual features are reliable estimates; (2) emotion ratings could be predicted by a small combination of perceptual features ...
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