'Visibility brings with it responsibility': Using a pragmatic performance approach to explore a political philosophy of technology

With the emergence, suspicion and social acceptance of ubiquitous communications technology thoroughly plumbed and the digital age already wondering what it is going to rename itself in light of ever more fluid and complex technologies, this paper asks: what can theatre and performance provide to the production of a political philosophy of technology? Using the work of Maurice Merleau-Ponty, Michel Foucault and an analysis of a recent inter-cultural adaptation of Jean Genet's The Maids, this study examines the politics of visible theatre technologies in performance and offers a pragmatic, or instrumentalist, approach to developing a political philosophy of technology

Auditory Spectrum-Based Pitched Instrument Onset Detection

In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well as pitch-based features. These features are often combined for maximizing detection performance. Here, the spectral flux and phase slope features are derived in the auditory framework and a novel fundamental frequency estimation algorithm based on auditory spectra is introduced. An onset detection algorithm is proposed, which processes and combines the aforementioned features at the decision level. Experiments are conducted on a dataset covering 11 pitched instrument types, consisting of 1829 onsets in total. Results indicate that auditory representations outperform various state-of-the-art approaches, with the onset detection algorithm reaching an F-measure of 82.6%

Spatial Consistency and Contextual Cues for Incidental Learning in Browser Design

This paper introduces the Backward Highlighting technique for mitigating an identified flaw in directional column-faceted browsers like iTunes. Further, the technique significantly enhances the information that can be learned from the columns and encourages further interaction with facet items that were previously restricted from use. After giving a detailed overview of faceted browsing approaches, the Backward Highlighting technique is described along with possible implementations. Two of these possible implementations are compared to a control condition to statistically prove the value of Backward Highlighting. The analysis produces design recommendations for implementing the Backward Highlighting technique within faceted browsers that choose the directional column approach. The paper concludes with future work on how to further improve on the statistically proven advantages provided by the Backward Highlighting technique

Music Maker – A Camera-based Music Making Tool for Physical Rehabilitation

The therapeutic effects of playing music are being recognized increasingly in the field of rehabilitation medicine. People with physical disabilities, however, often do not have the motor dexterity needed to play an instrument. We developed a camera-based human-computer interface called "Music Maker" to provide such people with a means to make music by performing therapeutic exercises. Music Maker uses computer vision techniques to convert the movements of a patient's body part, for example, a finger, hand, or foot, into musical and visual feedback using the open software platform EyesWeb. It can be adjusted to a patient's particular therapeutic needs and provides quantitative tools for monitoring the recovery process and assessing therapeutic outcomes. We tested the potential of Music Maker as a rehabilitation tool with six subjects who responded to or created music in various movement exercises. In these proof-of-concept experiments, Music Maker has performed reliably and shown its promise as a therapeutic device.National Science Foundation (IIS-0308213, IIS-039009, IIS-0093367, P200A01031, EIA-0202067 to M.B.); National Institutes of Health (DC-03663 to E.S.); Boston University (Dudley Allen Sargent Research Fund (to A.L.)