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Although one can see a certain convergence between the interaction designs of different notation editors, there is no general consensus or standard since new interaction paradigms keep appearing with most major software updates or new products. In this paper, we present the results from an online survey (n = 138) with standardized usability and user experience questionnaires. The users of digital notation editors were asked to fill out the System Usability Score, the AttrakDiff2 and the Liveness questionnaire. This provides insights into domain specific design problems with the goal to inform the design of future interfaces. Almost all music notation editors show clear deficiencies in overall usability. Furthermore, a detailed examination of the obtained metrics show specific dependencies of individual qualities, which are helpful to conduct further qualitative research.

Interaktion mit Musiknotation ist in der musikalischen Praxis allgegenwärtig, wird in der Forschung aber vor allem im Zusammenhang mit Notensatzprogrammen thematisiert. Das wird allerdings der Vielfalt an Notationsformen und Anwendungsszenarien, die über das reine Setzen der Noten hinausgehen, nicht gerecht. Der vorliegende Beitrag weitet den Blick auf interessante Impulse aus angrenzenden Forschungsfeldern und betrachtet den Design Space von musikalischer Notation auch abseits des klassischen Notensatzes. Ein Beitrag zur 9. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2023 Open Humanities Open Culture.

Music notation is a central part of higher music education. However, today there is very limited support for interactive music notation in Learning Management Systems (LMS), which hinders LMS adoption. Therefore the advantages of LMS are not widely used in musical subjects and the advancement of new forms of teaching is hindered. We are developing an interactive web based music notation editor, which we use in highly interactive, H5P-compliant task types to ensure interoperability with a variety of different LMS. This will result in a feature-complete LMS with interactive music notation that covers content creation, communication, assessment and administration. In this paper we will concentrate on the overall architecture of the project and present some insights from a pilot usability study we performed in earlier stages.

Das Forschungsgebiet der Innovativen Computerbasierten Musikinterfaces umfasst inzwischen und mit Zunahme der Miniaturisierung und vereinfachten Integration von Sensorik und Aktorik eine Vielfalt von Themengebieten. Dazu gehören u.a. neuartige Musikinstrumente, interaktive und teils kooperative Multitouch Anwendungen, 3-D-Sound, Audio-Video-Installationen und Performances. Es finden sich vielfältige Möglichkeiten in konkreten Anwendungsgebieten, wie auch im rein künstlerischen Ausdruck. Im ICMI-Workshop 2022 möchten wir gern den gesamten Bereich »Musikalischer Interaktion« betrachten und sprechen die unterschiedlichsten Zielgruppen in diesem spannenden Gebiet an. In der Regelmäßigkeit unserer Workshops möchten wir gern ein Forum bieten, um neue Ansätze und Forschungsvorhaben zur Music Interaction vorzustellen und zu diskutieren. Dabei ist es das primäre Ziel, die unterschiedlichen Expertengruppen, die sich meist unabhängig voneinander mit dieser Thematik befassen, einander näher zu bringen und in einer gemeinsamen Veranstaltung Ideen, Experimente und Entwicklungen kennen zu lernen und sich auszutauschen. Der ICMI-Workshop wurde auf der MuC seit 2008 sieben Mal durchgeführt und war dort stark nachgefragt. Eine Übersicht der Vorträge / Papers der vergangenenWorkshops findet man unter www.icmi-workshop.org. Das Konzept des ICMI-Workshops beinhaltet einen Vortrag einer herausragenden Person des Forschungsund Anwendungsfelds als Keynotespeaker.

In the course of editing musical works, musicologists regularly compare multiple sources of the same musical piece, such as composers' autographs, handwritten copies, and various prints. For efficient comparison, cross-source navigation is essential, enabling to quickly jump back and forth between multiple sources without losing the current musical position. In practice, measures are first annotated by hand in the individual source images and then related to each other. Our approach automates this time-consuming and error-prone process with the help of deep learning. For this purpose, we train a neural network that automatically finds bounding boxes of all measures in images. A second network is trained to compute the similarity between two measures to determine if they have the same musical content and should, therefore, be linked for navigation. Sequences of outputs from the second network are matched using Dynamic Time Warping to provide the final proposal of measure relationships, so-called concordances. In addition to cross-source navigation, the results can be used to spot structural differences across the sources which are essential for editorial work, so that musicologists can focus more on analytical tasks.

When a pianist is playing on a MIDI keyboard, the computer does not know with which hand a key was pressed. With the help of a Recurrent Neural Network (RNN), we assign played MIDI notes to one of the two hands. We compare our new approach with an existing heuristic algorithm and show that RNNs perform better. The solution is real-time capable and can be used via OSC from any programming environment. A non real-time capable variant provides slightly higher accuracy. Our solution can be used in music notation software to assign the left or right hand to the upper or lower staff automatically. Another application is live playing, where different synthesizer sounds can be mapped to the left and right hand.

Das Forschungsgebiet der Innovativen Computerbasierten Mu-sikinterfaces umfasst inzwischen und mit Zunahme der Miniaturi-sierung und vereinfachten Integration von Sensorik und Aktorik eine Vielfalt von Themengebieten. Dazu gehören u.a. neuartige Musikinstrumente, interaktive und teils kooperative Multitouch Anwendungen, 3-D-Sound, Audio-Video-Installationen und Per-formances. Es finden sich vielfältige Möglichkeiten in konkreten Anwendungsgebieten, wie auch im rein künstlerischen Ausdruck. Im ICMI-Workshop für 2019 möchten wir gern den gesamten Bereich »Musikalischer Interaktion« betrachten und sprechen die unterschiedlichsten Zielgruppen in diesem spannenden Gebiet an. In der Regelmäßigkeit unserer Workshops möchten wir gern ein Forum bieten, um neue Ansätze und Forschungsvorhaben zur Music Interaction vorzustellen und zu diskutieren. Dabei ist es das primäre Ziel, die unterschiedlichen Expertengruppen, die sich meist unabhängig voneinander mit dieser Thematik befassen, ei-nander näher zu bringen und in einer gemeinsamen Veranstal-tung Ideen, Experimente und Entwicklungen kennen zu lernen und sich auszutauschen.

Tabletop role-playing games are a collaborative narrative experience. Throughout gaming sessions, Ambient music and noises are frequently used to enrich and facilitate the narration. With AmbiDice we introduce a tangible interface and music generator specially devised for this application scenario. We detail the technical implementation of the device, the software architecture of the music system (AmbientMusicBox) and the scripting language to compose Ambient music and soundscapes. AmbiDice was presented to experienced players and gained positive feedback and constructive suggestions for further development.

Das Forschungsgebiet der Innovativen Computerbasierten Musikinterfaces umfasst inzwischen und mit Zunahme der Miniaturisierung und vereinfachten Integration von Sensorik und Aktorik eine Vielfalt von Themengebieten. Dazu gehören u.a. neuartige Musikinstrumente, interaktive und teils kooperative Multitouch Anwendungen, 3-D-Sound, Audio-Video-Installationen und Performances. Es finden sich vielfältige Möglichkeiten in konkreten Anwendungsgebieten, wie auch im rein künstlerischen Ausdruck. Im ICMI-Workshop für 2017 möchten wir gerne den gesamten Bereich »Musikalischer Interaktion« betrachten und sprechen die unterschiedlichsten Zielgruppen in diesem spannenden Gebiet an. In der Regelmäßigkeit unserer Workshops möchten wir gerne ein Forum bieten, um neue Ansätze und Forschungsvorhaben zur Music Interaction vorzustellen und zu diskutieren. Dabei ist es das primäre Ziel, die unterschiedlichen Expertengruppen, die sich meist unabhängig voneinander mit dieser Thematik befassen, einander näher zu bringen und in einer gemeinsamen Veranstaltung Ideen, Experimente und Entwicklungen kennen zu lernen und sich auszutauschen. Der ICMI-Workshop wurde bisher auf der M&C 2008, 2009, 2011, 2012 und 2015 durchgeführt und war dort stark nachgefragt. Eine Übersicht der Vorträge findet man unter www.icmi-workshop.org.

Der Beitrag liefert einen State-of-the-Art Report zur Nutzung von Neuronalen Netzen in computerbasierten Musikinterfaces.

With the rapid evolution of technology, sensor aided performances and installations have gained popularity. We identified a number of important criteria for stage usage and artistic experimentation. These are partially met by existing approaches, oftentimes trading off programmability for ease of use. We propose our new sensor interface SPINE-2 that presents a comprehensive solution to these stage requirements without that trade-off.

Physical computing platforms such as the Arduino have significantly simplified developing physical musical interfaces. However, those platforms typically target everyday programmers rather than composers and media artists. On the other hand, tangible user interface (TUI) toolkits, which provide an integrated, easy-to-use solution have not gained momentum in modern music creation. We propose a concept that hybridizes physical computing and TUI toolkit approaches. This helps to tackle typical TUI toolkit weaknesses, namely quick sensor obsolescence and limited choices. We developed a physical realization based on the idea of "universal pins," which can be configured to perform a variety of duties, making it possible to connect different sensor breakouts and modules. We evaluated our prototype by making performance measurements and conducting a user study demonstrating the feasibility of our approach.

Music ensembles have to synchronize themselves with a very high precision inorder to achieve the desired musical results. For that purpose the musicians donot only rely on their auditory perception but also perceive and interpret themovements and gestures of their ensemble colleges. In this paper we present aKinect-based method to analyze ensemble play based on head tracking. We discussfirst experimental results with a violin duo performance.

Recent advances in sensor technology provide new opportunities for applications that utilize the user's movement as an input source. This thesis focuses on movement analysis, which is a sub-area of a larger field concerned with the interpretation of sensor signals of human movement. Movement analysis can be used to provide feedback for training motor tasks, which is of interest for application areas such as rehabilitation, sports, and ergonomics. Consciously controllable, goal-directed movements, which we call primary movements, lead to slight movements in other parts of the body that are beyond conscious control (secondary movements). Secondary movements are generated due to the mechanical interaction with the environment and physiological dependencies of the body. This thesis contributes methods to distinguish between primary and secondary movements. This is necessary in order to provide high-quality feedback for motor tasks that show a significant amount of secondary movement. This can be the case when the secondary movements are large because of large reaction forces (e.g., when shooting a ball) or when the primary movements to execute the task are small (e.g., in various forms of handcraft or musical instrument performance). Furthermore, a precise distinction between primary and secondary movement can be necessary to check whether the user keeps a part of the body still (e.g., as required by a gymnastic exercise). Apart from sensor-based feedback, our results can also be used to improve current gesture recognition methods by ignoring secondary movement in the sensor signal to avoid that a secondary movement is misinterpreted as an execution of a gesture. The effectiveness of the proposed methods is shown in the context of pianist arm movements, which are particularly challenging to analyze. The distinction between primary and secondary movement in one joint of the arm is based on the measured movement in that particular joint, an estimation of key reaction force from MIDI data, and the movement in the other joints of the arm. In order to know on which arm the estimated key reaction force acts, it is necessary to determine which hand has played a note. For that purpose two methods are introduced: One method is based on MIDI; the other one uses data from inertial sensors in combination to MIDI. A third method based on Computer Vision, which was originally developed for sign language recognition, is evaluated here for tracking pianist hands. Based on the analysis methods, two pedagogical applications were developed: One application supports an existing piano pedagogical movement notation and checks whether the player's movement conforms to the indicated movement. A user study with piano students of a music university shows that potential users judge that the system is useful for the training of technique. The second application visualizes the sensor data and allows synchronizing different performances of the same piece, making it easy to spot differences where a closer examination may be beneficial.

Description

Measurement of pianists' arm movement provides a signal,which is composed of controlled movements and noise. Thenoise is composed of uncontrolled movement generated bythe interaction of the arm with the piano action and measurement error. We propose a probabilistic model for armtouch movements, which allows to estimate the amount ofnoise in a joint. This estimation helps to interpret the movement signal, which is of interest for augmented piano andpiano pedagogy applications.

Description

The MICON is an electronic music stand extending Maestro!, the latest in a series of interactive conducting exhibits that use real orchestral audio and video recordings. The MICON uses OpenGL-based rendering to display and animate score pages with a high degree of realism. It offers three different score display formats to match the user's level of expertise. A realtime animated visual cueing system helps users with their conducting. The MICON has been evaluated with music students.

Real-time information from microblogs like Twitter is useful for different applications such as market research, opinion mining, and crisis management. For many of those messages, location information is required to derive useful insights. Today, however, only around 1% of all tweets are explicitly geotagged. We propose the first multi-indicator method for determining (1) the location where a tweet was created as well as (2) the location of the user's residence. Our method is based on various weighted indicators, including the names of places that appear in the text message, dedicated location entries, and additional information from the user profile. An evaluation shows that our method is capable of locating 92% of all tweets with a median accuracy of below 30km, as well as predicting the user's residence with a median accuracy of below 5.1km. With that level of accuracy, our approach significantly outperforms existing work.

The introduction of open-plan offices in the 1960s with the intent of making the workplace more flexible, efficient, and team-oriented resulted in a higher noise floor level, which not only made concentrated work more difficult, but also caused physiological problems, such as increased stress, in addition to a loss of speech privacy. Irrelevant background human speech, in particular, has proven to be a major factor in disrupting concentration and lowering performance. Therefore, reducing the intelligibility of speech and has been a goal of increasing importance in recent years. One method employed to do so is the use of masking noises, which consists in emitting a continuous noise signal over a loudspeaker system that conceals the perturbing speech. Studies have shown that while effective, the maskers employed to date – normally filtered pink noise – are generally poorly accepted by users. The collaborative "Private Workspace" project, within the scope of which this thesis was carried out, attempts to develop a coupled, adaptive noise masking system along with a physical structure to be used for open-plan offices so as to combat these issues. There is evidence to suggest that nature sounds might be more accepted as masker, in part because they can have a visual object that acts as the source for the sound. Direct audio recordings are not recommended for various reasons, and thus the nature sounds must be synthesized. This work done consists of the synthesis of a sound texture to be used as a masker as well as its evaluation. The sound texture is composed of two parts: a wind-like noise synthesized with subtractive synthesis, and a leaf-like noise synthesized through granular synthesis. Different combinations of these two noises produced five variations of the masker, which were evaluated at different levels along with white noise and pink noise using a modified version of an Oldenburger Satztest to test for an affect on speech intelligibility and a questionnaire to asses its subjective acceptance. The goal was to find which of the synthesized noises works best as a speech masker. This thesis first uses a theoretical introduction to establish the basics of sound perception, psychoacoustic masking, and sound texture synthesis. The design of each of the noises, as well as their respective implementations in MATLAB, is explained, followed by the procedures used to evaluate the maskers. The results obtained in the evaluation are analyzed. Lastly, conclusions are drawn and future work is and modifications to the masker are proposed. RESUMEN. La introducción de las oficinas abiertas en los años 60 tenía como objeto flexibilizar el ambiente laboral, hacerlo más eficiente y que estuviera más orientado al trabajo en equipo. Como consecuencia, subió el nivel de ruido de fondo, que no sólo dificulta la concentración, sino que causa problemas fisiológicos, como el aumento del estrés, además de reducir la privacidad. Hay estudios que prueban que las conversaciones de fondo en particular tienen un efecto negativo en el nivel de concentración y disminuyen el rendimiento de los trabajadores. Por lo tanto, reducir la inteligibilidad del habla es uno de los principales objetivos en la actualidad. Un método empleado para hacerlo ha sido el uso de ruido enmascarante, que consiste en reproducir señales continuas de ruido a través de un sistema de altavoces que enmascare el habla. Aunque diversos estudios demuestran que es un método eficaz, los ruidos utilizados hasta la fecha (normalmente ruido rosa filtrado), no son muy bien aceptados por los usuarios. El proyecto colaborativo "Private Workspace", dentro del cual se engloba el trabajo realizado en este Proyecto Fin de Grado, tiene por objeto desarrollar un sistema de ruido enmascarador acoplado y adaptativo, además de una estructura física, para su uso en oficinas abiertas con el fin de combatir los problemas descritos anteriormente. Existen indicios de que los sonidos naturales son mejor aceptados, en parte porque pueden tener una estructura física que simule ser la fuente de los mismos. La utilización de grabaciones directas de estos sonidos no está recomendada por varios motivos, y por lo tanto los sonidos naturales deben ser sintetizados. El presente trabajo consiste en la síntesis de una textura de sonido (en inglés sound texture) para ser usada como ruido enmascarador, además de su evaluación. La textura está compuesta de dos partes: un sonido de viento sintetizado mediante síntesis sustractiva y un sonido de hojas sintetizado mediante síntesis granular. Diferentes combinaciones de estos dos sonidos producen cinco variaciones de ruido enmascarador. Estos cinco ruidos han sido evaluados a diferentes niveles, junto con ruido blanco y ruido rosa, mediante una versión modificada de un Oldenburger Satztest para comprobar cómo afectan a la inteligibilidad del habla, y mediante un cuestionario para una evaluación subjetiva de su aceptación. El objetivo era encontrar qué ruido de los que se han sintetizado funciona mejor como enmascarador del habla. El proyecto consiste en una introducción teórica que establece las bases de la percepción del sonido, el enmascaramiento psicoacústico, y la síntesis de texturas de sonido. Se explica a continuación el diseño de cada uno de los ruidos, así como su implementación en MATLAB. Posteriormente se detallan los procedimientos empleados para evaluarlos. Los resultados obtenidos se analizan y se extraen conclusiones. Por último, se propone un posible trabajo futuro y mejoras al ruido sintetizado.