Recordings of musical practices are kept in various public institutions and private depositories around the world. They constitute valuable data for ethnomusicological research and are substantial for the world's musical heritage. At the moment, there are no commonly used systems and standards for organizing, describing or categorizing these data, which makes their use difficult. In this paper, we discuss the required steps to make them findable, accessible, interoperable and reusable (FAIR), and outline action items to reach these goals. We show solutions that help researchers to manage their data over the whole research lifecycle and discuss the benefits of combining technologies from information science, music information retrieval, and linked data, with the aim of giving incentives for the ethnomusicology research community to actively participate in these developments in the future.

Die Tao verfügen über ein ganzheitliches Musikkonzept, das unlösbar mit allen Lebensbereichen verwoben ist. Wei-Ya Lin untersucht die Singpraxis der Tao daher anhand von ethnomusikologischen sowie sozial- und kulturanthropologischen Methoden und Ansätzen und fragt: Wie haben die Geister den Tao in früheren Zeiten das Singen beigebracht und wie kommunizieren sie, wenn jemand ein Tabu bricht? Was hat Singen mit der Nutzung von Naturressourcen zu tun? Und wie verändert sich das musikalische Verhalten im Lauf der Zeit? Dabei wird deutlich, dass ein tieferes Verständnis soziokultureller Transformationsprozesse nur erfolgen kann, wenn man berücksichtigt, dass zwischen Liedern, Geistern und Tabus wechselseitige Beziehungen bestehen.

How can performing be transformed into cognition? Knowing in Performing describes dynamic processes of artistic knowledge production in music and the performing arts. Knowing refers to how processual, embodied, and tacit knowledge can be developed from performative practices in music, dance, theatre, and film. By exploring the field of artistic research as a constantly transforming space for participatory and experimental artistic practices, this anthology points the way forward for researchers, artists, and decision-makers inside and outside universities of the arts.

Der Beitrag zeichnet den Übergang der Akademie zur Hochschule für Musik und darstellende Kunst Wien seit den 1950er Jahren nach, beleuchtet die Hintergründe rund um die Genese des Kunsthochschul-Organisationsgesetzes 1970 und gewährt Einblicke in die Anfangsphase der jungen Hochschule.

Session 1: Virtual Analog: JUDY NAJNUDEL, RÉMY MÜLLER, THOMAS HÉLIE and DAVID ROZE: Identification of Nonlinear Circuits As Port-Hamiltonian Systems | PIER PAOLO LA PASTINA, STEFANO D'ANGELO and LEONARDO GABRIELLI: Arbitrary-Order IIR Antiderivative Antialiasing | KURT JAMES WERNER: An Equivalent Circuit Interpretation of Antiderivative Antialiasing | MICHELE DUCCESCHI, STEFAN BILBAO and CRAIG J. WEBB: Non-Iterative Schemes for the Simulation of Nonlinear Audio Circuits | MOHAMMED DANISH, STEFAN BILBAO and MICHELE DUCCESCHI: Applications of Port Hamiltonian Methods to Non-Iterative Stable Simulations of the Korg35 and Moog 4-Pole VCF | FABIÁN ESQUEDA, BORIS KUZNETSOV AND JULIAN D. PARKER: Differentiable White-Box Virtual Analog Modeling | FRANÇOIS G. GERMAIN: Practical Virtual Analog Modeling Using Möbius Transforms | Session 2: Analysis and Manipulation: JASON NARADOWSKY: Amp-Space: A Large-Scale Dataset for Fine-Grained Timbre Transformation | JULIAN NERI, PHILIPPE DEPALLE and ROLAND BADEAU: Damped Chirp Mixture Estimation via Nonlinear Bayesian Regression | LEONARDO FIERRO and VESA VÄLIMÄKI: SiTraNo: A MATLAB App for Sines-Transients-Noise Decomposition of Audio Signals | MARCELO CAETANO and PHILIPPE DEPALLE: On the Estimation of Sinusoidal Parameters via Parabolic Interpolation of Scaled Magnitude Spectra | Session 3: Audio Processing and Effects: PIER PAOLO LA PASTINA and STEFANO D'ANGELO: Optimal Integer Order Approximation of Fractional Order Filters | CHAMP C. DARABUNDIT and JONATHAN S. ABEL: Conformal Maps for the Discretization of Analog Filters Near the Nyquist Limit | SEBASTIAN LAGUERRE and GARY P. SCAVONE: Simulating a Hexaphonic Pickup Using Parallel Comb Filters for Guitar Distortion | YURI DE PRA, FEDERICO FONTANA and STEFANO PAPETTI: Interacting with Digital Audio Effects Through a Haptic Knob with Programmable Resistance | SEBASTIAN ROSENZWEIG, SIMON SCHWÄR, JONATHAN DRIEDGER and MEINARD MÜLLER: Adaptive Pitch-Shifting with Applications to Intonation Adjustment in A Cappella Recordings | JON FAGERSTRÖM, SEBASTIAN J. SCHLECHT and VESA VÄLIMÄKI: One-to-Many Conversion for Percussive Samples | Session 4: Physical Modeling: VINAYAK AGARWAL, MADDIE CUSIMANO, JAMES TRAER and JOSH MCDERMOTT: Object-Based Synthesis of Scraping and Rolling Sounds Based on Non-Linear Physical Constraints | SILVIN WILLEMSEN, STEFAN BILBAO, MICHELE DUCCESCHI and STEFANIA SERAFIN: Dynamic Grids for Finite-Difference Schemes in Musical Instrument Simulations | SILVIN WILLEMSEN, STEFAN BILBAO, MICHELE DUCCESCHI and STEFANIA SERAFIN: A Physical Model of the Trombone Using Dynamic Grids for Finite-Difference Schemes | BRIAN HAMILTON: Air Absorption Filtering Method Based on Approximate Green's Function for Stokes' Equation | MARIUS GEORGE ONOFREI, SILVIN WILLEMSEN and STEFANIA SERAFIN: Real-Time Implementation of a Friction Drum Inspired Instrument Using Finite Difference Schemes | VADIM ZAVALISHIN and JULIAN D. PARKER: On the Equivalence of Integrator- and Differentiator-Based Continuous- and Discrete-Time Systems | Session 5: Spatial Audio and Artificial Reverberation: NARA HAHN, FRANK SCHULTZ and SASCHA SPORS: Higher-Order Anti-Derivatives of Band Limited Step Functions for the Design of Radial Filters in Spherical Harmonics Expansions | JACOB MCQUILLAN and MAARTEN VAN WALSTIJN: Modal Spring Reverb Based on Discretisation of the Thin Helical Spring Model | RAIMUNDO GONZALEZ, ARCHONTIS POLITIS and TAPIO LOKKI: Spherical Decomposition of Arbitrary Scattering Geometries for Virtual Acoustic Environments | JANIS HELDMANN and SEBASTIAN J. SCHLECHT: The Role of Modal Excitation in Colorless Reverberation | LEO MCCORMACK, ARCHONTIS POLITIS and VILLE PULKKI: Parametric Spatial Audio Effects Based on the Multi-Directional Decomposition of Ambisonic Sound Scenes | Session 6: Synthesis: JOSEPH TURIAN, JORDIE SHIER, GEORGE TZANETAKIS, KIRK MCNALLY and MAX HENRY: One Billion Audio Sounds From GPU-Enabled Modular Synthesis | PRATEEK VERMA and CHRIS CHAFE: A Generative Model for Raw Audio Using Transformer Architectures | DARIO SANFILIPPO and JULIAN D. PARKER: Combining Zeroth and First-Order Analysis with Lagrange Polynomials to Reduce Artefacts in Live Concatenative Granulation | TIAGO FERNANDES TAVARES, THALES ROEL P. PESSANHA, GUSTAVO NISHIHARA and GUILHERME ZANCHETTA L. AVILA: Alloy Sounds: Non-Repeating Sound Textures with Probabilistic Cellular Automata | GERARD ROMA, PIERRE ALEXANDRE TREMBLAY and OWEN GREEN: Graph-Based Audio Looping and Granulation | GEORG ESSL: Topologizing Sound Synthesis via Sheaves | Session 7: Machine Learning and Music Information Retrieval: DOMENICO STEFANI and LUCA TURCHET: Bio-Inspired Optimization of Parametric Onset Detectors | GWENDAL LE VAILLANT, THIERRY DUTOIT and SÉBASTIEN DEKEYSER: Improving Synthesizer Programming From Variational Autoencoders Latent Space | ALEKSI PEUSSA, EERO-PEKKA DAMSKÄGG, THOMAS SHERSON, STYLIANOS I. MIMILAKIS, LAURI JUVELA, ATHANASIOS GOTSOPOULOS and VESA VÄLIMÄKI: Exposure Bias and State Matching in Recurrent Neural Network Virtual Analog Models | XIANKE WANG, WEI XU, JUANTING LIU, WEIMING YANG and WENQING CHENG: Transition-Aware: A More Robust Approach for Piano Transcription | NAOTAKE MASUDA and DAISUKE SAITO: Quality Diversity for Synthesizer Sound Matching | XIANKE WANG, WEI XU, JUANTING LIU, WEIMING YANG and WENQING CHENG: An Audio-Visual Fusion Piano Transcription Approach Based on Strategy

Die kooperative Studie MUDIL beforscht die Arbeitsfelder von Musiklehrenden an Schulen und Musikschulen unter den Bedingungen von Distance Learning während der Covid-19-Krise in Österreich. Der vorliegende Forschungsbericht stellt ausgewählte Ergebnisse einer österreichweiten, quantitativen online-Befragung im Sommer 2020 dar, in der Rückmeldungen von 1158 Lehrenden aus Musikschulen und Regelschulen der Sekundarstufe in ganz Österreich und Südtirol ausgewertet werden konnten. Inhalt sind neben einer sozio-demografischen Einordnung der Befragungsergebnisse die technischen und rechtlichen Rahmenbedingungen, die pädagogischen Entwicklungen in Unterricht und Lernen sowie damit verbundene Probleme und Chancen, sowie Ausblicke auf zukünftige Entwicklungen mit Einschätzungen von Potentialen und Risiken.

Beside transmitting musical meaning from composer to reader, symbolic music notation affords the dynamic addition of layers of information by annotation. This allows music scores to serve as rudimentary communication frameworks. Music encodings bring these affordances into the digital realm; though annotations may be represented as digital pen-strokes upon a score image, they must be captured using machine-interpretable semantics to fully benefit from this transformation. This is challenging, as annotators’ requirements are heterogeneous, varying both across different types of user (e.g., musician, scholar) and within these groups, depending on the specific use-case. A hypothetical all-encompassing tool catering to every conceivable annotation type, even if it were possible to build, would vastly complicate user interaction. This additional complexity would significantly increase cognitive load and impair usability, particularly in dynamic real-time usage contexts, e.g., live annotation during music rehearsal or performance. To address this challenge, we present a social data infrastructure that facilitates the creation of use-case specific annotation toolkits. Its components include a selectable-score module that supports customisable click-and-drag selection of score elements (e.g., notes, measures, directives); the Web Annotations data model, extended to support the creation of custom, Web-addressable annotation types supporting the specification and (re-)use of annotation palettes; and the Music Encoding and Linked Data (MELD) Javascript client library, used to build interfaces that map annotation types to rendering and interaction handlers. We have extended MELD to support the Solid platform for social Linked Data, allowing annotations to be privately stored in user-controlled Personal Online Datastores (Pods), or selectively shared or published. To demonstrate the feasibility of our proposed approach, we present annotation interfaces employing the outlined infrastructure in three distinct use-cases: scholarly communication; music rehearsal; and rating during music listening.