Michael Casey

Efficient methods of biodiversity assessment and monitoring are central to ecological research and crucial in conservation management; technological advances in remote acoustic sensing inspire new approaches. In line with the emerging field of Soundscape Ecology, the acoustic approach is based on the rationale that the ecological processes occurring within a landscape are tightly linked to and reflected in the high-level structure of the patterns of sounds emanating from those landscapes ¿ the soundscape.

Here we present an extension to the studyforrest dataset – a versatile resource for studying the behavior of the human brain in situations of real-life complexity (http://studyforrest.org). This release adds more high-resolution, ultra high-field (7 Tesla) functional magnetic resonance imaging (fMRI) data from the same individuals. The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm.

We investigated the perception of music in a cognitive musicology study, employing behavioral methods to examine general associative patterns--i.e. the propensity for subjects to recruit associations when listening to music, reminiscent of synaesthetic cross-wiring (Cytowic, 2009). Although non-Synaesthetic associations to music are less explored, experiments such as Köhler’s (1929) linguistic “Kiki, Boulba” study, demonstrated associations in non-synaesthetes, supporting the hypothesis that general listeners engage cross-sensorial connections.

Our research explores theories based upon past behavioural studies and FMRI scans with Synaesthetes and general listeners. FMRI experiments have revealed that the cross-modal associations to sounds in Synaesthetes are less pronounced, yet still present in the general population. The results of our psycho-musicology study with 40 Synaesthetes and 40 non-Synaesthetes reveal a quasi-Synaesthetic [Nikolic, 2014] spectrum extending to general listeners, similar to culturally founded Synaesthesia [Kohler].

This paper investigates perceptual relationships between art in the auditory and visual domains. First, we conducted a behavioral experiment asking subjects to assess similarity between 10 musical recordings and 10 works of abstract art. We found a significant degree of agreement across subjects as to which i mages correspond to which audio, even though neither the audio nor the images possessed semantic content. Secondly, we sought to find the relationship between audio and images within a defined feature space that correlated with the subjective similarity judgments.

The top 40 chart is a popular resource used by listeners to select and purchase music. Previous work on automatic hit song prediction focused on Western pop music. However, pop songs from different parts of the world exhibit significant differences.

Complexity of music audio signals creates an access prollem to specific musical objects or structures within the source samples. Instead of employing more commonly used audio analysis or production techniques to access features, we describe extraction of sub-mixtures from real-world audio using a Probabilistic Latent Component Analysis-based de- composition tool for music composition.

The “groove” of a song correlates with enjoyment and bodily movement. Recent work has shown that humans often agree whether a song does or does not have groove and how much groove a song has. It is therefore useful to develop algorithms that characterize the quality of groove across songs. We evaluate three unsupervised tempo-invariant models for measuring pairwise musical groove similarity: A temporal model, a timbre-temporal model, and a pitch-timbre-temporal model.

Content-based analysis of video using audio and visual features has previously been used for the automatic tasks of scene/shot segmentation and video summarization. We present new work that extends this research to automatically extract and compare the narrative structure of feature films, discover patterns in the relationship of music, sound, and image, and classify films according to their director using audio, visual, and joint audio-visual features.