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Musical signals exhibit periodic temporal structure that create the sensation of rhythm. In order to model, analyze, and retrieve musical signals it is important to automatically extract rhythmic information. To somewhat simplify the problem, automatic algorithms typically only extract information about the main beat of the signal which can be loosely defined as the regular periodic sequence of pulses corresponding to where a human would tap his foot while listening to the music. In these algorithms, the beat is characterized by its frequency (tempo), phase (accent locations) and a confidence measure about its detection. The main focus of this paper is the concept of Beat Strength, which will be loosely defined as one rhythmic characteristic that could allow to discriminate between two pieces of music having the same tempo. Using this definition, we might say that a piece of Hard Rock has a higher beat strength than a piece of Classical Music at the same tempo. Characteristics related to Beat Strength have been implicitely used in automatic beat detection algorithms and shown to be as important as tempo information for music classification and retrieval. In the work presented in this paper, a user study exploring the perception of Beat Strength was conducted and the results were used to calibrate and explore automatic Beat Strength measures based on the calculation of Beat Histograms.

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This paper proposes the sonification of the activity of a computer system that allows the user to monitor the basic performance parameters of the system, like CPU load, read and write activity of the hard disk or network traffic. Although, current computer systems still produce acoustic background noise, future and emerging computer systems will be more and more optimized with respect to their noise emission. In contrast to most of the concepts of auditory feedback, which present a particular sound as a feedback to a user’s command, the proposed feedback is mediated by the running computer system. The user’s interaction stimulates the system and hence the resulting feedback offers more realistic information about the current states of performance of the system. On the one hand the proposed sonification can mimic the acoustical behavior of operating components inside a computer system, while on the other hand, new qualities can be synthesized that enrich interaction with the device. Different forms of sound effects and generation for the proposed auditory feedback are realized to experiment with the usage in an environment of silent computer systems.

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