Auditory Scene Analysis

By Albert S. Bregman. 2001

2,496 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Speech and Hearing, Signal Processing

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Citations in the corpus

Music Source Separation in the Waveform Domain (2019, background): “His framework for auditory scene analysis [Bregman, 1990] spawned its computational counterpart, trying to reproduce or model accomplishments of the brains with algorithmic means [Wang and Brown, 2006], in particular regarding source separation capabilities.”
Audio-visual speech scene analysis: characterization of the dynamics of unbinding and rebinding the McGurk effect. (2015, background): “It is classically considered that auditory scene analysis involves a default grouped state 898 followed by a possible build-up of auditory segregation (Bregman, 1990).”
Divide and Conquer: A Deep CASA Approach to Talker-Independent Monaural Speaker Separation (2019, background): “A traditional approach to monaural speech separation is computational auditory scene analysis (CASA) [37], which is inspired by human auditory scene analysis (ASA) mechanisms [3].”
Why otoliths? Insights from inner ear physiology and fisheries biology (2005, background): “…pointed out that a major role of the auditory system is to provide an animal (or human) with a general sense of its acoustic environment and that this auditory scene (Bregman 1991) is of considerable value in providing an animal with information about things happening around it, but out of sight.”
Does English coronal place assimilation create lexical ambiguity (2002, background): “Subsequent researchers including Julesz and Hirsh (1972) and Bregman (1990) have argued that these principles play a role in the organization of auditory events. Listeners could group on the Gestalt principle of similarity. Labial place cues associated with a labialized coronal might group naturally”
On the optimality of ideal binary time-frequency masks (2008, background): “Bregman [1] proposed an influential theory, called auditory scene analysis (ASA), to explain this ability.”
A Supervised Learning Approach to Monaural Segregation of Reverberant Speech (2009, background): “Such a goal has been shown to still be reasonable when room reverberation is present [39, 44].”
The time dimension for scene analysis (2005, background): “The network demonstrates a set of psychophysical phenomena, including dependency of stream segregation on spectral and temporal proximity, sequential capturing, and competition among different perceptual organizations [13].”
POOR-PITCH SINGING IN THE ABSENCE OF "TONE DEAFNESS" (2007, background): “, 2002), given that dissonance can create frequency modulations that promote segregation (Bregman, 1990).”
Mate choice rules in animals (2006, background): “The other sounds, or the auditory scene, from which a call must be parsed, for example, can influence the perception of that signal (Bregman 1990).”
Listening and Human Communication in the 21st Century (2011, methodology): “…pitch, and rhythm (Pisoni, 1987) which facilitate auditory streaming and segregating the incoming sound waves into perceptual groups (Summerfield and Culling, 1992) using auditory Gestalt principles of similarity, proximity, common fate, and continuity (Bregman, 1978, 1981, 1990; Styles, 2005).”