A computer implementation of psychoacoustic grouping rules

We are building a computer model of sound organization and understanding in human listeners. In particular, we would like to be able to detect and locate acoustic events that will be perceived as separate objects. Our model aims to duplicate this aspect of the auditory system although the level of correspondence is speculative given our current state of knowledge. We describe an implementation of grouping rules corresponding to the psychoacoustic cues of harmonicity, common onset, continuity and proximity. We increase the system's robustness by adding a second layer of grouping that looks for corroboration between primary groupings. We believe that such a system of repeated hierarchic grouping is critical for the successful modeling of auditory functions

Map, Trigger, Score, Procedure: machine-listening paradigms in live-electronics

Since the advent of real-time computer music environments, composers have increasingly incorporated DSP analysis, synthesis, and processing algorithms in their creative practices. Those processes became part of interactive systems that use real-time computational tools in musical compositions that explore diverse techniques to generate, spatialize, and process instrumental/vocal sounds. Parallel to the development of these tools and the expansion of DSP methods, new techniques focused on sound/musical information extraction became part of the tools available for music composition. In this context, this article discusses the creative use of Machine Listening and Musical Information Retrieval techniques applied in the composition of live-electronics works. By pointing out some practical applications and creative approaches, we aim to circumscribe, in a general way, the strategies for employing Machine Listening and Music Information Retrieval techniques observed in a set of live-electronics pieces, categorizing four compositional approaches, namely: mapping, triggering, scoring, and procedural paradigms of application of machine listening techniques in the context of live-electronics music compositions

Music-listening systems

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2000.Includes bibliographical references (p. [235]-248).When human listeners are confronted with musical sounds, they rapidly and automatically orient themselves in the music. Even musically untrained listeners have an exceptional ability to make rapid judgments about music from very short examples, such as determining the music's style, performer, beat, complexity, and emotional impact. However, there are presently no theories of music perception that can explain this behavior, and it has proven very difficult to build computer music-analysis tools with similar capabilities. This dissertation examines the psychoacoustic origins of the early stages of music listening in humans, using both experimental and computer-modeling approaches. The results of this research enable the construction of automatic machine-listening systems that can make human-like judgments about short musical stimuli. New models are presented that explain the perception of musical tempo, the perceived segmentation of sound scenes into multiple auditory images, and the extraction of musical features from complex musical sounds. These models are implemented as signal-processing and pattern-recognition computer programs, using the principle of understanding without separation. Two experiments with human listeners study the rapid assignment of high-level judgments to musical stimuli, and it is demonstrated that many of the experimental results can be explained with a multiple-regression model on the extracted musical features. From a theoretical standpoint, the thesis shows how theories of music perception can be grounded in a principled way upon psychoacoustic models in a computational-auditory-scene-analysis framework. Further, the perceptual theory presented is more relevant to everyday listeners and situations than are previous cognitive-structuralist approaches to music perception and cognition. From a practical standpoint, the various models form a set of computer signal-processing and pattern-recognition tools that can mimic human perceptual abilities on a variety of musical tasks such as tapping along with the beat, parsing music into sections, making semantic judgments about musical examples, and estimating the similarity of two pieces of music.Eric D. Scheirer.Ph.D

Underconstrained stochastic representations for top-down computational auditory scene analysis

I propose a structure for the first stage of a computer system capable of performing complex auditory scene analysis similar to that accomplished by human listeners. This structure contains the following innovations over previous approaches: (1) Sound is represented as discrete elements drawn from an overcomplete vocabulary encompassing both tonal and less structured sounds, designed to highlight the interdependence in the acoustic energy. (2) Through the redundancy of the basis this analysis permits and indeed requires the imposition of additional constraints, which provides for the incorporation of top-down or context-sensitive factors. (3) A modular architecture operates on an analysis-by-synthesis principle, where processes are invoked until the representation adequately accounts for the observed sound. A common goodness-of-fit criterion allows for future expansion of the system with new explanation rules, new representational elements and more abstract levels of analysis. Some initial results of applying these ideas to scenes consisting of noise bursts and dense environmental sound are presented