Stefano Fasciani

• Støckert, Robin; Bergsland, Andreas; Fasciani, Stefano & Jensenius, Alexander Refsum (2020). Student active learning in a two campus organisation. eLearning and Software for Education.  ISSN 2066-026X.  1, s 612- 620 . doi: 10.12753/2066-026X-20-080
• Copiaco, Abigail; Ritz, Christian H; Fasciani, Stefano & Abdulaziz, Nidhal (2019). Scalogram Neural Network Activations with Machine Learning for Domestic Multi-channel Audio Classification. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).  ISSN 2162-7843. . doi: 10.1109/ISSPIT47144.2019.9001814
• Copiaco, Abigail; Ritz, Christian; Abdulaziz, Nidhal & Fasciani, Stefano (2020). Identifying Optimal Features for Multi-channel Acoustic Scene Classification, In Eesa M Bastaki & Husameldin Mukhtar (ed.),  2019 2nd International Conference on Signal Processing and Information Security (ICSPIS).  IEEE.  ISBN 978-1-7281-3873-2.  Conference Paper.
• Fasciani, Stefano & Vohra, Manohar (2019). Towards a High-Performance Platform for Sonic Interaction Interfaces, In Isabel Barbancho; Lorenzo J. Tardón; Alberto Peinado & Ana M. Barbancho (ed.),  SMC 2019 Proceedings of the 16th Sound & Music Computing Conference.  Society for Sound and Music Computing.  ISBN 978-84-09-08518-7.  Paper.  s 97 - 104 Fulltekst i vitenarkiv. Vis sammendrag

  In this paper we introduce a hardware platform to proto- type interfaces of demanding sonic interactive systems. We target applications featuring a large array of analog sensors requiring data acquisition and transmission to computers at fast rates, with low latency, and high band- width. This work is part of an ongoing project which aims to provide designers with a cost effective and acces- sible platform for fast prototyping of complex interfaces for sonic interactive systems or musical instruments. The high performances are guaranteed by a SoC FPGA. The functionality of the platform can be customized without requiring significant technical expertise. In this paper, we discuss the principles, the current design, and the prelim- inary evaluation against common microcontroller-based platforms. The proposed platform can sample up to 96 analog channels at rates up to 24 kHz and stream the data via UDP to computers with a sub millisecond latency.

• Vohra, Manohar & Fasciani, Stefano (2019). PYNQ-Torch: a framework to develop PyTorch accelerators on the PYNQ platform. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).  ISSN 2162-7843. . doi: 10.1109/ISSPIT47144.2019.9001806
• Fasciani, Stefano (2018). Spectral Granular Synthesis, In Tae Hong Park & Doo-Jin Ahn (ed.),  Proceedings of the 2018 International Computer Music Conference.  The International Computer Music Association.  ISBN 0-9845274-7-8.  Paper.  s 99 - 103 Vis sammendrag

  This article introduces a granular synthesis algorithm in which grains of sound are processed in the frequency domain and combined at spectral level. In particular, each grain contributes to the sound synthesis with its magnitude spectrum only. Phase is reconstructed using spectrogram inversion techniques which support real- time computation. With this method, windowing and overlapping grains of regular size is no longer required. The algorithm presents a large number of parameters available for the dynamic manipulation of the synthetic timbre. Algorithm implementations are detailed in the paper, including comparison with traditional time-domain against the proposed frequency-domain granulation strategies.

• Fasciani, Stefano & Rahman, Habibur (2018). Tangible Virtual Patch Cords, In Tae Hong Park & Doo-Jin Ahn (ed.),  Proceedings of the 2018 International Computer Music Conference.  The International Computer Music Association.  ISBN 0-9845274-7-8.  Paper.  s 316 - 321 Vis sammendrag

  This paper presents a system to tangibly manipulate the virtual patching cords in graphical programming environments, such as Max and Pure Data. The system includes a physical interface, a communication protocol, and a software library, providing physical extension of the graphical programming paradigm. The interface includes a patch bay with connectors representing signal inlet and outlets from the programming environment. When inlets and outlets are connected with patching cords, equivalent virtual connections are created at runtime. The system supports one-to-many and many-to-one connections with different signal combination schemes. The design of the hardware and software components of the current prototype is detailed in the paper, as well as possible use of the system for programming and live performances.

• Fasciani, Stefano & Wyse, Lonce (2018). Vocal control of sound synthesis personalized by unsupervised machine listening and learning. Computer Music Journal.  ISSN 0148-9267.  42(1), s 37- 59 . doi: 10.1162/comj_a_00450 Vis sammendrag

  In this article we describe a user-driven adaptive method to control the sonic response of digital musical instruments using information extracted from the timbre of the human voice. The mapping between heterogeneous attributes of the input and output timbres is determined from data collected through machine-listening techniques and then processed by unsupervised machine-learning algorithms. This approach is based on a minimum-loss mapping that hides any synthesizer-specific parameters and that maps the vocal interaction directly to perceptual characteristics of the generated sound. The mapping adapts to the dynamics detected in the voice and maximizes the timbral space covered by the sound synthesizer. The strategies for mapping vocal control to perceptual timbral features and for automating the customization of vocal interfaces for different users and synthesizers, in general, are evaluated through a variety of qualitative and quantitative methods.

Se alle arbeider i Cristin

• Fasciani, Stefano; Jensenius, Alexander Refsum; Støckert, Robin & Xambó, Anna (2020). The MCT Portal: an infrastructure, a laboratory and a pedagogical tool.
• Støckert, Robin; Bergsland, Andreas; Fasciani, Stefano & Jensenius, Alexander Refsum (2020). Student active learning in a two campus organisation. Vis sammendrag

  Higher education is facing disruptive changes in many fields. Students wants to have the option of learning anywhere, anytime and in any format. Universities need to develop and deliver to future students a complete learning ecosystem. At the same time universities are facing challenges such as growing costs and the pressure to give the students the knowledge, competence, skills and ability to continuously adapt to future job environments. As a consequence, many universities are investigating new ways of collaboration and sharing resources to cater to the demands of students, industry and society. An example of this collaboration is a new joint master between the two largest Universities in Norway: University of Oslo (UiO) and Norwegian University of Science and Technology (NTNU). In this paper, we present the lessons learned from almost two years of teaching and learning in the new joint master's programme, "Music, Communication and Technology" (MCT), between NTNU and UiO. This programme is a run in a two-campus learning space built as a two-way, audio-visual, high-quality, low-latency communication channel between the two campuses, called "The Portal". Moreover, MCT is the subject of research for the SALTO (Student Active Learning in a Two campus Organisation) project, where novel techniques in teaching and learning are explored, such as team-based learning (TBL), flipped classroom, and other forms of student active learning. Educational elements in this master, provides the student with 21st century skills and deliver knowledge within humanities, entrepreneurship and technology. We elaborate on the technical, pedagogical and learning space-related challenges toward delivering teaching and learning in these cross-university settings. The paper concludes with a set of strategies that can be used to improve student active learning in different scenarios.

Se alle arbeider i Cristin