A music search engine for therapeutic gait training

Li, Zhonghua; Xiang, Qiao-Liang; Hockman, Jason; Yang, Junzheng; Chen, Yu; Fujinaga, Ichiro; Wang, Ye

doi:10.1145/1873951.1874037

Cited by 9 publications

(5 citation statements)

References 6 publications

(6 reference statements)

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“…More inclusive research projects can incorporate systematic user studies. Examples are collaborations with music archives that provide access for streaming users, exploration of the use of music to achieve certain emotional states (Demetriou et al, 2016), or the application in therapeutic contexts (Li et al, 2010). Including users into a research process may help avoid conflicts with communities (see Example 1) by allowing them to participate as catalysts for research that matters (Wagstaff, 2012).…”

Section: Resultsmentioning

confidence: 99%

Ethical Dimensions of Music Information Retrieval Technology

Holzapfel¹,

Sturm²,

Coeckelbergh

2018

Transactions of the International Society for Music Information Retrieval

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This article examines ethical dimensions of Music Information Retrieval (MIR) technology. It uses practical ethics (especially computer ethics and engineering ethics) and socio-technical approaches to provide a theoretical basis that can inform discussions of ethics in MIR. To help ground the discussion, the article engages with concrete examples and discourse drawn from the MIR field. This article argues that MIR technology is not value-neutral but is influenced by design choices, and so has unintended and ethically relevant implications. These can be invisible unless one considers how the technology relates to wider society. The article points to the blurring of boundaries between music and technology, and frames music as "informationally enriched" and as a "total social fact." The article calls attention to biases that are introduced by algorithms and data used for MIR technology, cultural issues related to copyright, and ethical problems in MIR as a scientific practice. The article concludes with tentative ethical guidelines for MIR developers, and calls for addressing key ethical problems with MIR technology and practice, especially those related to forms of bias and the remoteness of the technology development from end users.

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Section: Resultsmentioning

confidence: 99%

Ethical Dimensions of Music Information Retrieval Technology

Holzapfel¹,

Sturm²,

Coeckelbergh

2018

Transactions of the International Society for Music Information Retrieval

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“…7 Online demonstration video: http://youtu.be/wyFXbUTdW-Y The music dimensions selected in i 2 MUSE are those frequently used in music searches. These dimensions are also widely included in music applications for everyday activities (e.g., running [13,14] and driving [15]) as well as therapeutic treatments (e.g., walking training for gait disorders [8,16]). By adjusting different parameters and weights for each dimension, i 2 MUSE is able to meet various music information needs and application scenarios.…”

Section: Proposal Of I 2 Musementioning

confidence: 99%

“…Tempo measures the average speed of the music in beats per minute (BPM) and beat strength the prominence of beats in the music. Tempo and beat strength are important in various scenarios related to user activities and contexts [8,13,14,15], and the categorical dimensions are among the top music tag groups in describing general musical concepts.…”

Section: Music Dimensions and Data Collectionmentioning

confidence: 99%

“…[8,9]; also described in Section 1), in this paper we only implemented and compared our proposed i 2 MUSE with another baseline MMSE. This baseline MMSE had the same music dimensions and categories as i 2 MUSE but without those feedback functions, including automatic category suggestion/un-suggestion, weight adjustment, and result preview.…”

Section: Configurationmentioning

confidence: 99%

“…A few multidimensional music search engines (MMSEs) have been proposed by researchers that support multidimensional queries directly on a graphical interface [1,6,7,8,9]. For example, MuMa 5 includes dimensions such as chord, genre, mood and date [9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bridging the User Intention Gap

Zhu

Cai

Jian-gang

et al. 2014

Proceedings of the First International Workshop on Internet-Scale Multimedia Management

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Music is inherently abstract and multidimensional. However, existing music search engines are usually not convenient or too complicated for users to create multidimensional music queries, leading to the intention gap between users' music information needs and the input queries. In this paper, we present a novel content-based music search engine, the Intelligent & Interactive Multidimensional mUsic Search Engine (i 2 MUSE), which enables users to input music queries with multiple dimensions efficiently and effectively. Six musical dimensions, including tempo, beat strength, genre, mood, instrument, and vocal, are explored in this study. Users can begin a query from any dimension and interact with the system to organize the query. Once the parameters of some dimensions have been set, i 2 MUSE is able to intelligently highlight a suggested parameter and gray out an un-suggested parameter for every other dimension, helping users express their music intentions and avoid parameter conflicts in the query. In addition, i 2 MUSE provides a real-time illustration of the percentage of matched tracks in the database. Users can also set the relative weight of each specified dimension. We have conducted a pilot user study with 30 subjects and validated the effectiveness and usability of i 2 MUSE.

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