VISR—A Versatile Open Software Framework for Audio Signal Processing

Franck A, Fazi FM. VISR—A Versatile Open Software Framework for Audio Signal Processing. In: AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science. Audio Engineering Society; 2018. Paper P9-2. Available from: https://aes.org/publications/elibrary-page/?id=19628

@inproceedings{Franck2018_19628,
  author = {Franck, Andreas and Fazi, Filippo Maria},
  title = {{VISR—A Versatile Open Software Framework for Audio Signal Processing}},
  booktitle = {AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science},
  note = {Paper P9-2},
  year = {2018},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19628}
}

TY  - CPAPER
TI  - VISR—A Versatile Open Software Framework for Audio Signal Processing
AU  - Franck, Andreas
AU  - Fazi, Filippo Maria
T2  - AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science
M1  - Paper P9-2
PY  - 2018
DA  - 2018/07/06
UR  - https://aes.org/publications/elibrary-page/?id=19628
PB  - Audio Engineering Society
LA  - en
AB  - Software plays an increasingly important role in spatial and object-based audio. Realtime and interactive rendering is often needed to subjectively evaluate and demonstrate algorithms, requiring signi?cant implementation effort and often impeding the reproducibility of scienti?c research. In this paper we present the VISR (Versatile Interactive Scene Renderer) – a modular, open-source software framework for audio processing. VISR enables systematic reuse of DSP functionality, rapid prototyping in C++ or Python, and integration into the typical work?ow of audio research and development from initial implementation and of?ine objective evaluation to subjective testing. This paper provides a practical, example-based introduction to the VISR framework. This is demonstrated with an interconnected example, from algorithm design and implementation, dynamic binaural auralization, to a subjective test.
ER  -