Digital audio and especially music collections are becoming a major part of the average computer user experience. Large digital audio collections of sound effects are also used by the movie and animation industry. Research areas that utilize large audio collections include: Auditory Display, Bioacoustics, Computer Music, Forensics, and Music Cognition.|
In order to develop more sophisticated tools for interacting with large digital audio collections, research in Computer Audition algorithms and user interfaces is required. In this work a series of systems for manipulating, retrieving from, and analysing large collections of audio signals will be described. The foundation of these systems is the design of new and the application of existing algorithms for automatic audio content analysis. The results of the analysis are used to build novel 2D and 3D graphical user interfaces for browsing and interacting with audio signals and collections. The proposed systems are based on techniques from the fields of Signal Processing, Pattern Recognition, Information Retrieval, Visualization and Human Computer Interaction. All the proposed algorithms and interfaces are integrated under MARSYAS, a free software framework designed for rapid prototyping of computer audition research. In most cases the proposed algorithms have been evaluated and informed by conducting user studies.
New contributions of this work to the area of Computer Audition include: a general multifeature audio texture segmentation methodology, feature extraction from mp3 compressed data, automatic beat detection and analysis based on the Discrete Wavelet Transform and musical genre classification combining timbral, rhythmic and harmonic features. Novel graphical user interfaces developed in this work are various tools for browsing and visualizing large audio collections such as the Timbregram, TimbreSpace, GenreGram, and Enhanced Sound Editor.