Search results for "segmentation density"

showing 2 items of 2 documents

Interaction features for prediction of perceptual segmentation:Effects of musicianship and experimental task

2016

As music unfolds in time, structure is recognised and understood by listeners, regardless of their level of musical expertise. A number of studies have found spectral and tonal changes to quite successfully model boundaries between structural sections. However, the effects of musical expertise and experimental task on computational modelling of structure are not yet well understood. These issues need to be addressed to better understand how listeners perceive the structure of music and to improve automatic segmentation algorithms. In this study, computational prediction of segmentation by listeners was investigated for six musical stimuli via a real-time task and an annotation (non real-tim…

Visual Arts and Performing ArtsComputer scienceSpeech recognitionComputationmedia_common.quotation_subjectsegmentation taskBoundary (topology)Novelty detection050105 experimental psychologyTask (project management)03 medical and health sciences0302 clinical medicinePerception0501 psychology and cognitive sciencesSegmentationmedia_commonStructure (mathematical logic)05 social sciencesNoveltyboundary strengthta6131segmentation density030217 neurology & neurosurgeryMusicnovelty detectionmusical training
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Effects of musicianship and experimental task on perceptual segmentation

2015

The perceptual structure of music is a fundamental issue in music psychology that can be systematically addressed via computational models. This study estimated the contribution of spectral, rhythmic and tonal descriptors for prediction of perceptual segmentation across stimuli. In a real-time task, 18 musicians and 18 non-musicians indicated perceived instants of significant change for six ongoing musical stimuli. In a second task, 18 musicians parsed the same stimuli using audio editing software to provide non-real-time segmentation annotations. We built computational models based on a non-linear fuzzy integration of basic and interaction descriptors of local musical novelty. We found tha…

musicianshipsegmentointimusic psychologyMusical trainingmuusikkousInformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)segmentationmusiikkipsykologiaSegmentation densitySegmentation taskaudio-based computational modeling
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