From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Music Information Retrieval in Live Coding: A Theoretical Framework

The work presented in this article has been partly conducted while the first author was at Georgia Tech from 2015–2017 with the support of the School of Music, the Center for Music Technology and Women in Music Tech at Georgia Tech. Another part of this research has been conducted while the first author was at Queen Mary University of London from 2017–2019 with the support of the AudioCommons project, funded by the European Commission through the Horizon 2020 programme, research and innovation grant 688382. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Music information retrieval (MIR) has a great potential in musical live coding because it can help the musician–programmer to make musical decisions based on audio content analysis and explore new sonorities by means of MIR techniques. The use of real-time MIR techniques can be computationally demanding and thus they have been rarely used in live coding; when they have been used, it has been with a focus on low-level feature extraction. This article surveys and discusses the potential of MIR applied to live coding at a higher musical level. We propose a conceptual framework of three categories: (1) audio repurposing, (2) audio rewiring, and (3) audio remixing. We explored the three categories in live performance through an application programming interface library written in SuperCollider, MIRLC. We found that it is still a technical challenge to use high-level features in real time, yet using rhythmic and tonal properties (midlevel features) in combination with text-based information (e.g., tags) helps to achieve a closer perceptual level centered on pitch and rhythm when using MIR in live coding. We discuss challenges and future directions of utilizing MIR approaches in the computer music field

Factors in human recognition of timbre lexicons generated by data clustering

Since the development of sound recording technologies, the palette of sound timbres available for music creation was extended way beyond traditional musical instruments. The organization and categorization of timbre has been a common endeavor. The availability of large databases of sound clips provides an opportunity for obtaining datadriven timbre categorizations via content-based clustering. In this article we describe an experiment aimed at understanding what factors influence the process of learning a given clustering of sound samples. We clustered a large database of short sound clips, and analyzed the success of participants in assigning sounds to the “correct” clusters after listening to a few examples of each. The results of the experiment suggest a number of relevant factors related both to the strategies followed by users and to the quality measures of the clustering solution, which can guide the design of creative applications based on audio clip clustering

Evaluation of spoken document retrieval for historic speech collections

The re-use of spoken word audio collections maintained by audiovisual archives is severely hindered by their generally limited access. The CHoral project, which is part of the CATCH program funded by the Dutch Research Council, aims to provide users of speech archives with online, instead of on-location, access to relevant fragments, instead of full documents. To meet this goal, a spoken document retrieval framework is being developed. In this paper the evaluation efforts undertaken so far to assess and improve various aspects of the framework are presented. These efforts include (i) evaluation of the automatically generated textual representations of the spoken word documents that enable word-based search, (ii) the development of measures to estimate the quality of the textual representations for use in information retrieval, and (iii) studies to establish the potential user groups of the to-be-developed technology, and the first versions of the user interface supporting online access to spoken word collections