Sonic Visualiser

Sonic Visualiser
Name	Sonic Visualiser
Developer	Centre for Digital Music, Queen Mary University of London
Released	2003
Programming language	C++
Operating system	Windows, macOS, Linux
Genre	Audio analysis, Music information retrieval
License	GNU GPL

Sonic Visualiser Sonic Visualiser is an open-source application for viewing and analyzing the contents of music audio files. It is developed by the Centre for Digital Music at Queen Mary University of London and used in academic, archival, and production contexts involving musicology, signal processing, and music information retrieval. The software enables detailed visual inspection, time-frequency analysis, annotation, and plugin-driven feature extraction.

Overview

Sonic Visualiser was created to support research in music technology and to provide a graphical front end for analysis tools used in projects affiliated with the Centre for Digital Music, Queen Mary University of London, the Alan Turing Institute, the BBC, the British Library, the European Research Council, and the Arts and Humanities Research Council. It is often used alongside applications and institutions such as Audacity, Praat, MATLAB, Python, R, the Max/MSP environment, the Music Information Retrieval Evaluation eXchange (MIREX), the International Society for Music Information Retrieval, the Audio Engineering Society, the Institute of Electrical and Electronics Engineers, and the Association for Computing Machinery. Sonic Visualiser interoperates with data sets and initiatives like MusicBrainz, the Million Song Dataset, the British Library Sound Archive, the Library of Congress, the Internet Archive, the European Broadcasting Union, and the World Intellectual Property Organization.

Features

The program provides spectrum displays, waveform views, piano roll overlays, chromagrams, beat and onset detection, tempo and key estimation, and annotated layers. Feature extraction capabilities are comparable to tools used in projects at MIT, Stanford, Harvard, Oxford, Cambridge, Yale, and Columbia, and integrate with libraries and formats like Vamp plugins, LADSPA, LV2, JACK, ALSA, Core Audio, ASIO, FLAC, WAV, AIFF, MPEG, Ogg Vorbis, and MIDI. Visualization options and export features make it useful for practitioners affiliated with Dolby Laboratories, Harman International, SoundCloud, Spotify, Apple, Google, Microsoft Research, IBM Research, Sony, and Universal Music Group.

Development and History

Development began in the early 2000s under principal investigators at Queen Mary University of London who collaborated with researchers from IRCAM, CCRMA at Stanford, the Centre Pompidou, the Max Planck Institute for Empirical Aesthetics, and the Centre for New Music and Audio Technologies at UC Berkeley. Funding and collaborative projects included grants from the European Commission, the Engineering and Physical Sciences Research Council, the Wellcome Trust, the Leverhulme Trust, and joint ventures with the British Broadcasting Corporation and BBC R&D. Sonic Visualiser has evolved through contributions from academics and engineers associated with University of Oxford, University of Cambridge, University of Edinburgh, McGill University, University of Toronto, and KTH Royal Institute of Technology. It has been showcased at conferences and workshops organized by the International Society for Music Information Retrieval, the Society for Musicology in Ireland, the Conference on Computer Vision and Pattern Recognition, NeurIPS, ISMIR, AES conventions, and the International Conference on Acoustics, Speech, and Signal Processing.

Architecture and Plugins

The application is written in C++ and uses Qt for its graphical user interface, with audio I/O handled through libraries favored by projects at Steinberg, Native Instruments, Ableton, Avid Technology, and Propellerhead Software. Plugin architecture relies on the Vamp plugin API, enabling third-party modules developed by researchers at IRCAM, IRCAM's STMS Lab, Queen Mary, IRCAM’s analysis teams, and independent developers. Plugins and scripting interoperate with environments and tools such as SuperCollider, Pure Data, Max, Ruby, Lua, Python bindings used by NumPy and SciPy, and research prototypes from institutions like Google Brain, DeepMind, Facebook AI Research, and OpenAI. Support for annotation and metadata integrates with standards and projects such as Music Ontology, Dublin Core, IEEE 1599, Music Encoding Initiative, and the Text Encoding Initiative.

Use Cases and Applications

Sonic Visualiser is used for tasks in ethnomusicology, historical sound preservation, forensic audio, acoustic ecology, audio restoration, transcription, beat tracking, key estimation, melody extraction, and corpus creation. Practitioners from conservatories and institutions like the Royal College of Music, Juilliard School, Berklee College of Music, Conservatoire de Paris, and the Royal Academy of Music use it alongside resources from the British Library, New York Public Library, Smithsonian Institution, Getty Research Institute, and national archives. It supports research projects connected to initiatives at CERN, NASA, ESA, National Science Foundation, and health-related projects funded by the National Institutes of Health and the Wellcome Trust when audio analysis is relevant.

Reception and Adoption

Academic adoption is widespread across universities and labs including Queen Mary University of London, University of Oxford, University of Cambridge, Stanford University, Massachusetts Institute of Technology, Princeton University, ETH Zurich, TU Berlin, KTH, McGill, and RIKEN. The tool is cited in publications appearing in journals and conferences such as Journal of the Acoustical Society of America, IEEE/ACM Transactions on Audio, Speech, and Language Processing, Computer Music Journal, PLOS ONE, Nature Communications, Science Advances, ISMIR proceedings, AES Journal, and Transactions of the International Society for Music Information Retrieval. Industry and cultural institutions—BBC, British Library, Smithsonian, Spotify, Apple, Google, and Dolby—have referenced or used workflows that include Sonic Visualiser in research, archiving, and product development contexts.

Category:Audio software