Search (4 results, page 1 of 1)

0.024683168 = sum of:
  0.0072458386 = product of:
    0.036229193 = sum of:
      0.036229193 = weight(_text_:been in 2845) [ClassicSimilarity], result of:
        0.036229193 = score(doc=2845,freq=2.0), product of:
          0.18374448 = queryWeight, product of:
            3.5691874 = idf(docFreq=3386, maxDocs=44218)
            0.05148076 = queryNorm
          0.1971716 = fieldWeight in 2845, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5691874 = idf(docFreq=3386, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2845)
    0.2 = coord(1/5)
  0.01743733 = product of:
    0.03487466 = sum of:
      0.03487466 = weight(_text_:22 in 2845) [ClassicSimilarity], result of:
        0.03487466 = score(doc=2845,freq=2.0), product of:
          0.18027684 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05148076 = queryNorm
          0.19345059 = fieldWeight in 2845, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2845)
    0.5 = coord(1/2)

Abstract

The music information retrieval (MIR) community has long understood the role of evaluation as a critical component for successful information retrieval systems. Over the past several years, it has also become evident that user-centered evaluation based on realistic tasks is essential for creating systems that are commercially marketable. Although user-oriented research has been increasing, the MIR field is still lacking in holistic, user-centered approaches to evaluating music services beyond measuring the performance of search or classification algorithms. In light of this need, we conducted a user study exploring how users evaluate their overall experience with existing popular commercial music services, asking about their interactions with the system as well as situational and personal characteristics. In this paper, we present a qualitative heuristic evaluation of commercial music services based on Jakob Nielsen's 10 usability heuristics for user interface design, and also discuss 8 additional criteria that may be used for the holistic evaluation of user experience in MIR systems. Finally, we recommend areas of future user research raised by trends and patterns that surfaced from this user study.

Date

17. 3.2016 19:22:15

0.014105613 = product of:
  0.028211227 = sum of:
    0.028211227 = product of:
      0.14105614 = sum of:
        0.14105614 = weight(_text_:themes in 3006) [ClassicSimilarity], result of:
          0.14105614 = score(doc=3006,freq=2.0), product of:
            0.3309713 = queryWeight, product of:
              6.429029 = idf(docFreq=193, maxDocs=44218)
              0.05148076 = queryNorm
            0.42618844 = fieldWeight in 3006, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              6.429029 = idf(docFreq=193, maxDocs=44218)
              0.046875 = fieldNorm(doc=3006)
      0.2 = coord(1/5)
  0.5 = coord(1/2)

Abstract

User studies in the music information retrieval (MIR) domain tend to be exploratory and qualitative in nature, involving a small number of users, which makes it difficult to derive broader implications for system design. In order to fill this gap, we conducted a large-scale user survey questioning various aspects of people's music information needs and behaviors. In particular, we investigated if general music users' needs and behaviors have significantly changed over time by comparing our current survey results with a similar survey conducted in 2004. In this paper, we present the key findings from the survey data and discuss 4 emergent themes-(a) the shift in access and use of personal music collections; (b) the growing need for tools to support collaborative music seeking, listening, and sharing; (c) the importance of "visual" music experiences; and (d) the need for ontologies for providing rich contextual information. We conclude by making specific recommendations for improving the design of MIR systems and services.

0.008718665 = product of:
  0.01743733 = sum of:
    0.01743733 = product of:
      0.03487466 = sum of:
        0.03487466 = weight(_text_:22 in 4218) [ClassicSimilarity], result of:
          0.03487466 = score(doc=4218,freq=2.0), product of:
            0.18027684 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05148076 = queryNorm
            0.19345059 = fieldWeight in 4218, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4218)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The discovery and retrieval of video games in library and information systems is, by and large, dependent on a limited set of descriptive metadata. Noticeably missing from this metadata are classifications of visual style-despite the overwhelmingly visual nature of most video games and the interest in visual style among video game users. One explanation for this paucity is the difficulty in eliciting consistent judgements about visual style, likely due to subjective interpretations of terminology and a lack of demonstrable testing for coinciding judgements. This study presents a taxonomy of video game visual styles constructed from the findings of a 22-participant cataloging user study of visual styles. A detailed description of the study, and its value and shortcomings, are presented along with reflections about the challenges of cultivating consensus about visual style in video games. The high degree of overall agreement in the user study demonstrates the potential value of a descriptor like visual style and the use of a cataloging study in developing visual style taxonomies. The resulting visual style taxonomy, the methods and analysis described herein may help improve the organization and retrieval of video games and possibly other visual materials like graphic designs, illustrations, and animations.

0.004347503 = product of:
  0.008695006 = sum of:
    0.008695006 = product of:
      0.04347503 = sum of:
        0.04347503 = weight(_text_:been in 3321) [ClassicSimilarity], result of:
          0.04347503 = score(doc=3321,freq=2.0), product of:
            0.18374448 = queryWeight, product of:
              3.5691874 = idf(docFreq=3386, maxDocs=44218)
              0.05148076 = queryNorm
            0.23660593 = fieldWeight in 3321, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5691874 = idf(docFreq=3386, maxDocs=44218)
              0.046875 = fieldNorm(doc=3321)
      0.2 = coord(1/5)
  0.5 = coord(1/2)

Abstract

Music Information Retrieval (MIR) evaluation has traditionally focused on system-centered approaches where components of MIR systems are evaluated against predefined data sets and golden answers (i.e., ground truth). There are two major limitations of such system-centered evaluation approaches: (a) The evaluation focuses on subtasks in music information retrieval, but not on entire systems and (b) users and their interactions with MIR systems are largely excluded. This article describes the first implementation of a holistic user-experience evaluation in MIR, the MIREX Grand Challenge, where complete MIR systems are evaluated, with user experience being the single overarching goal. It is the first time that complete MIR systems have been evaluated with end users in a realistic scenario. We present the design of the evaluation task, the evaluation criteria and a novel evaluation interface, and the data-collection platform. This is followed by an analysis of the results, reflection on the experience and lessons learned, and plans for future directions.