Download 3D graphics tools for sound collections
Most of the current tools for working with sound work on single soundfiles, use 2D graphics and offer limited interaction to the user. In this paper we describe a set of tools for working with collections of sounds that are based on interactive 3D graphics. These tools form two families: sound analysis visualization displays and model-based controllers for sound synthesis algorithms. We describe the general techniques we have used to develop these tools and give specific case studies from each family. Several collections of sounds were used for development and evaluation. These are: a set of musical instrument tones, a set of sound effects, a set of FM radio audio clips belonging to several music genres, and a set of mp3 rock song snippets.
Download Human Perception and Computer Extraction of Musical Beat Strength
Musical signals exhibit periodic temporal structure that create the sensation of rhythm. In order to model, analyze, and retrieve musical signals it is important to automatically extract rhythmic information. To somewhat simplify the problem, automatic algorithms typically only extract information about the main beat of the signal which can be loosely defined as the regular periodic sequence of pulses corresponding to where a human would tap his foot while listening to the music. In these algorithms, the beat is characterized by its frequency (tempo), phase (accent locations) and a confidence measure about its detection. The main focus of this paper is the concept of Beat Strength, which will be loosely defined as one rhythmic characteristic that could allow to discriminate between two pieces of music having the same tempo. Using this definition, we might say that a piece of Hard Rock has a higher beat strength than a piece of Classical Music at the same tempo. Characteristics related to Beat Strength have been implicitely used in automatic beat detection algorithms and shown to be as important as tempo information for music classification and retrieval. In the work presented in this paper, a user study exploring the perception of Beat Strength was conducted and the results were used to calibrate and explore automatic Beat Strength measures based on the calculation of Beat Histograms.