Perception of touch quality in piano tones.

Both timbre and dynamics of isolated piano tones are determined exclusively by the speed with which the hammer hits the strings. This physical view has been challenged by pianists who emphasize the importance of the way the keyboard is touched. This article presents empirical evidence from two perception experiments showing that touch-dependent sound components make sounds with identical hammer velocities but produced with different touch forms clearly distinguishable. The first experiment focused on finger-key sounds: musicians could identify pressed and struck touches. When the finger-key sounds were removed from the sounds, the effect vanished, suggesting that these sounds were the primary identification cue. The second experiment looked at key-keyframe sounds that occur when the key reaches key-bottom. Key-bottom impact was identified from key motion measured by a computer-controlled piano. Musicians were able to discriminate between piano tones that contain a key-bottom sound from those that do not. However, this effect might be attributable to sounds associated with the mechanical components of the piano action. In addition to the demonstrated acoustical effects of different touch forms, visual and tactile modalities may play important roles during piano performance that influence the production and perception of musical expression on the piano.

An e-Research approach to Web-scale music analysis.

The growing quantity of digital recorded music available in large-scale resources such as the Internet archive provides an important new resource for musical analysis. An e-Research approach has been adopted in order to create a very substantive web-accessible corpus of musical analyses in a common framework for use by music scholars, students and beyond, and to establish a methodology and tooling that will enable others to add to the resource in the future. The enabling infrastructure brings together scientific workflow and Semantic Web technologies with a set of algorithms and tools for extracting features from recorded music. It has been used to deliver a prototype system, described here, that demonstrates the utility of LINKED DATA for enhancing the curation of collections of music signal data for analysis and publishing results that can be simply and readily correlated to these and other sources. This paper describes the motivation, infrastructure design and the proof-of-concept case study and reflects on emerging e-Research practice as researchers embrace the scale of the Web.

A comparative study of staff removal algorithms.

This paper presents a quantitative comparison of different algorithms for the removal of stafflines from music images. It contains a survey of previously proposed algorithms and suggests a new skeletonization based approach. We define three different error metrics, compare the algorithms with respect to these metrics and measure their robustness with respect to certain image defects. Our test images are computer-generated scores on which we apply various image deformations typically found in real-world data. In addition to modern western music notation our test set also includes historic music notation such as mensural notation and lute tablature. Our general approach and evaluation methodology is not specific to staff removal, but applicable to other segmentation problems as well.