About This Issue

In this issue’s first article, Mattias Sköld describes his notation system called Sound Notation, which is an adaptation of Lasse Thoresen’s spectromorphological analysis notation. Sound Notation is similar to traditional Western staff notation but is designed to accommodate electronic sounds by summarizing their acoustical characteristics, such as spectral width, spectrum components, amplitude envelope, and other time-varying aspects. In previous publications, Sköld has described the notation’s use for analyzing electroacoustic music. Here, he focuses on its utility in composition. A central goal is to allow an electroacoustic composition to be represented as an abstraction amenable to different realizations, just as traditional notation represents instrumental and vocal compositions whose ultimate sound relies on different performers' interpretations. The article also presents the data format, similar to that of MIDI messages, that underlies his software for algorithmically generating Sound Notation scores.Reflecting the topic on this issue’s front cover, the article by Sullivan, Wanderley, and Guastavino describes a workshop whose participants, all expert musicians, imagined fictional digital music instruments (DMIs) that they would like to play. The participants then constructed rough physical mockups of these imaginary DMIs and presented them to the other workshop members for discussion. Following the workshop, the authors subjected transcriptions of the videorecorded presentations to qualitative data analysis. They identified themes that at least half of the participants mentioned. These themes suggest a desire for a balance between novelty, on the one hand, and exploiting features of existing instruments, on the other. The themes also evince an enthusiasm for flexibility and versatility in aspects such as control mapping, signal mixing and routing, and modules that a performer can easily configure. The authors then derived a corresponding set of high-level design specifications that could be of practical use to other DMI designers.Front cover. An image-processed composite of four figures from the article by Sullivan, Wanderley, and Guastavino. Various participants in the authors' design workshop display or assemble 3-D mockups of new performance interfaces they have envisioned.The third article, by McCall et al., similarly presents results from analyzing the output of participants in a program. In this case, the participants were not expert musicians, but middle-school students in a virtual summer camp that taught “computer science plus music.” The students were instructed in the use of two contrasting software applications for creating music using simple application programming interfaces (APIs). One application used a note-oriented paradigm, in which the user creates music by programmatically specifying note sequences to feed to a synthesizer. The other used the paradigm of a digital audio workstation (DAW) and thus focused on programmatically assembling and processing sound files. The authors discuss their analyses of the students' creations. For example, they found that the note-based computational platform may encourage a focus on low-level features of the music, whereas the DAW-like platform may direct attention to larger-scale musical features. They also found that some of the correlations between the curriculum’s music concepts and its computer science concepts were common to both software paradigms, but most were specific to one or the other.We move to the realm of music information retrieval for the article by Zehren, Alunno, and Bientinesi. They tackle an important problem for the automatic generation of a DJ mix, i.e., an uninterrupted series of songs whose endings and beginnings overlap and that are often adjusted to have matching tempi. A “switch point” is the position during a cross-fade between two songs at which the second song becomes prominent. The particular problem the authors investigate is how to determine automatically the best candidate switch points near the beginning of a given song. Their solution involves combining expert knowledge—a set of rules resulting from interviews with professional DJs—with a data-driven approach that gathers statistics from a dataset of songs containing manual annotations of switch points.Ross Feller’s Reviews section examines two recently released albums: one by Matthew Burtner and the other by the Contemporary Noise Ensemble. In the Products of Interest section, Margaret Cahill presents announcements of four audio interfaces, a mixer/recorder, a MIDI foot controller, a breath and motion controller, a Kyma audio processing unit, four audio software plug-ins, an Android control app, a Mac audio routing app, and a variety of microphones.—Douglas KeislarBack cover. A flowchart from the article by Zehren, Alunno, and Bientinesi, depicting their two techniques for determining switch points.