Analyzing Visual Mappings of Traditional and Alternative Music Notation

In this paper, we postulate that combining the domains of information visualization and music studies paves the ground for a more structured analysis of the design space of music notation, enabling the creation of alternative music notations that are tailored to different users and their tasks. Hence, we discuss the instantiation of a design and visualization pipeline for music notation that follows a structured approach, based on the fundamental concepts of information and data visualization. This enables practitioners and researchers of digital humanities and information visualization, alike, to conceptualize, create, and analyze novel music notation methods. Based on the analysis of relevant stakeholders and their usage of music notation as a mean of communication, we identify a set of relevant features typically encoded in different annotations and encodings, as used by interpreters, performers, and readers of music. We analyze the visual mappings of musical dimensions for varying notation methods to highlight gaps and frequent usages of encodings, visual channels, and Gestalt laws. This detailed analysis leads us to the conclusion that such an under-researched area in information visualization holds the potential for fundamental research. This paper discusses possible research opportunities, open challenges, and arguments that can be pursued in the process of analyzing, improving, or rethinking existing music notation systems and techniques.Comment: 5 pages including references, 3rd Workshop on Visualization for the Digital Humanities, Vis4DH, IEEE Vis 201

A hybrid neural network based speech recognition system for pervasive environments

One of the major drawbacks to using speech as the input to any pervasive environment is the requirement to balance accuracy with the high processing overheads involved. This paper presents an Arabic speech recognition system (called UbiqRec), which address this issue by providing a natural and intuitive way of communicating within ubiquitous environments, while balancing processing time, memory and recognition accuracy. A hybrid approach has been used which incorporates spectrographic information, singular value decomposition, concurrent self-organizing maps (CSOM) and pitch contours for Arabic phoneme recognition. The approach employs separate self-organizing maps (SOM) for each Arabic phoneme joined in parallel to form a CSOM. The performance results confirm that with suitable preprocessing of data, including extraction of distinct power spectral densities (PSD) and singular value decomposition, the training time for CSOM was reduced by 89%. The empirical results also proved that overall recognition accuracy did not fall below 91%

PLAYING WITH THE EDGE: TIPPING POINTS AND THE ROLE OF TONALITY

International audienceThis article centers on the phenomenon of tipping points-a case of extreme pulse elasticity-in music performance, and the dynamic interplay between tonal structure and musical timing. The article presents the idea and principles of tipping points. Examples illustrate three types of global and local tipping points: melodic, boundary, and cadential. Focusing on cadential tipping points, the article considers the role of tonality in a number of examples, thus bridging the subject of tipping points and prior work on the modeling of tonality. The spiral array model for tonality is described, including how the model traces the dynamics of tonal perception. A real-time implementation of the model is applied to cadential tipping point examples to visualize the effect of tipping points on tonal perception. The analyses show how tipping points influence tonal perception-clarifying, focusing, and exploiting harmonic function, in the case of cadential tipping points, to evoke tension and shape narrative structure

Goniometers are a Powerful Acoustic Feature for Music Information Retrieval Tasks

Goniometers, also known as Phase Scopes or Vector Scopes, are audio metering tools that help music producers and mixing engineers monitor spatial aspects of a music mix, such as the stereo panorama, the width of single sources, the amount and diffuseness of reverberation as well as phase cancellations that may occur on the sweet-spot and in a mono-mixdown. In addition, they implicitly inform about the dynamics of the sound. Self-organizing maps trained with a goniometer, are consulted to explore the usefulness of this acoustic feature for music information retrieval tasks. One can see that goniometers are able to classify different genres and cluster a single album. The advantage of goniometers is the causality: Music producers and mixing engineers consciously consult goniometers to reach their desired sound, which is not the case for other acoustic features, from Zero-Crossing Rate to Mel-Frequency Cepstral Coefficients

Applying Acoustical and Musicological Analysis to Detect Brain Responses to Realistic Music: A Case Study

Music information retrieval (MIR) methods offer interesting possibilities for automatically identifying time points in music recordings that relate to specific brain responses. However, how the acoustical features and the novelty of the music structure affect the brain response is not yet clear. In the present study, we tested a new method for automatically identifying time points of brain responses based on MIR analysis. We utilized an existing database including brain recordings of 48 healthy listeners measured with electroencephalography (EEG) and magnetoencephalography (MEG). While we succeeded in capturing brain responses related to acoustical changes in the modern tango piece Adios Nonino, we obtained less reliable brain responses with a metal rock piece and a modern symphony orchestra musical composition. However, brain responses might also relate to the novelty of the music structure. Hence, we added a manual musicological analysis of novelty in the musical structure to the computational acoustic analysis, obtaining strong brain responses even to the rock and modern pieces. Although no standardized method yet exists, these preliminary results suggest that analysis of novelty in music is an important aid to MIR analysis for investigating brain responses to realistic music.Peer reviewe