Effective everyday hearing requires the auditory system to organize auditory input into perceptual streams corresponding to objects of interest. Changes in this process may be responsible for age-related deterioration in the capacity to effectively hear important sounds masked by background noise. Younger (18-25) and older (55+) adults with healthy hearing listened to 10-second intervals of a simple pattern of “ABA” tone triplets. The ABA patterns are used as a model of real-world auditory streaming, because they are initially perceived as one integrated stream, and over time are reorganized into two segregated streams. Participants performed a target-detection task designed to index their perceptual organization of the tones, which does not depend on potentially-biased, subjective judgment (Thompson, Carlyon, & Cusack, 2011). Complex tones with narrowly-spaced, unresolvable frequency components were used in this experiment to control for age-related decreases in frequency selectivity. Both groups demonstrated a capacity for segregating the A and B tones based on differences in harmonic spacing, as predicted. However, despite our acoustic controls the older adults showed significantly less segregation of the 6ST stimuli, indicating that there are additional age-related changes in auditory streaming, which make them less likely to segregate in response to harmonic spacing differences. Additionally, older adults showed significantly better overall performance on the task than younger adults, indicating that the age differences are not simply due to age-related deficits in task execution. The ABA intervals were presented either continuously, or with 5-second interruptions prior to each trial that have previously been shown to “reset” perceptual streaming back to an integrated percept (Cusack, Deeks, Aikman, & Carlyon, 2004). For both age groups interruptions preceding the ABA intervals were shown to be capable of resulting in decreased segregation, as predicted. Targets were presented at 4 time points (2, 4, 6, and 8 seconds) in order to test for age differences in the time course of streaming. In the results for the 8-semitone stimuli, we observed strong evidence for delayed build-up in older adults, in response to the Gap condition. However, this evidence was not statistically conclusive and future experiments are needed determine the effect’s validity. / Thesis (Master, Psychology) -- Queen's University, 2011-09-20 10:50:27.01

The objective of this dissertation research is to identify sounds that grab a listener's attention. These sounds that draw a person's attention are sounds that are considered salient. The focus here will be on investigating the role of saliency in the auditory attentional process. In order to identify these salient sounds, we have developed a computational auditory saliency model inspired by our understanding of the human auditory system and auditory perception. By identifying salient sounds we can obtain a better understanding of how sounds are processed by the auditory system, and in particular, the key features contributing to sound salience. Additionally, studying the salience of different auditory stimuli can lead to improvements in the performance of current computational models in several different areas, by making use of the information obtained about what stands out perceptually to observers in a particular scene. Auditory saliency also helps to rapidly sort the information present in a complex auditory scene. Since our resources are finite, not all information can be processed equally. We must, therefore, be able to quickly determine the importance of different objects in a scene. Additionally, an immediate response or decision may be required. In order to respond, the observer needs to know the key elements of the scene. The issue of saliency is closely related to many different areas, including scene analysis. The thesis provides a comprehensive look at auditory saliency. It explores the advantages and limitations of using auditory saliency models through different experiments and presents a general computational auditory saliency model that can be used for various applications.

How do we know that a melody is a melody? In other words, how does the human brain extract melody from a polyphonic musical context? This thesis begins with a theoretical presentation of musical auditory scene analysis (ASA) in the context of predictive coding and rule-based approaches and takes methodological and analytical steps to evaluate selected components of a proposed integrated framework for musical ASA, unified by prediction. Predictive coding has been proposed as a grand unifying model of perception, action and cognition and is based on the idea that brains process error to refine models of the world. Existing models of ASA tackle distinct subsets of ASA and are currently unable to integrate all the acoustic and extensive contextual information needed to parse auditory scenes. This thesis proposes a framework capable of integrating all relevant information contributing to the understanding of musical auditory scenes, including auditory features, musical features, attention, expectation and listening experience, and examines a subset of ASA issues - timbre perception in relation to musical training, modelling temporal expectancies, the relative salience of musical parameters and melody extraction - using probabilistic approaches. Using behavioural methods, attention is shown to influence streaming perception based on timbre more than instrumental experience. Using probabilistic methods, information content (IC) for temporal aspects of music as generated by IDyOM (information dynamics of music; Pearce, 2005), are validated and, along with IC for pitch and harmonic aspects of the music, are subsequently linked to perceived complexity but not to salience. Furthermore, based on the hypotheses that a melody is internally coherent and the most complex voice in a piece of polyphonic music, IDyOM has been extended to extract melody from symbolic representations of chorales by J.S. Bach and a selection of string quartets by W.A. Mozart.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 156-168).

We are capable of effortlessly parsing a complex scene presented to us. In order to do this, we must segregate objects from each other and from the background. While this process has been extensively studied in vision science, it remains relatively less understood in auditory science. This thesis sought to characterize the neuroelectric correlates of auditory scene analysis using electroencephalography. Chapter 2 determined components evoked by first-order energy boundaries and second-order pitch boundaries. Chapter 3 determined components evoked by first-order and second-order discontinuous motion boundaries. Both of these chapters focused on analysis of event-related potential (ERP) waveforms and time-frequency analysis. In addition, these chapters investigated the contralateral nature of a negative ERP component. These results extend the current knowledge of auditory scene analysis by providing a starting point for discussing and characterizing first-order and second-order boundaries in an auditory scene. / x, 90 leaves : col. ill. ; 29 cm

Thesis (Ph.D.)--Texas Christian University, 2007. / Title from dissertation title page (viewed Jul. 27, 2007). Includes abstract. Includes bibliographical references.

No description available.

The information age has brought with it a dual problem. In the first place, the ready access to mechanisms to capture and store vast amounts of data in all forms (text, audio, image and video), has resulted in a continued demand for ever more efficient means to store and transmit this data. In the second, the rapidly increasing store demands effective means to structure and access the data in an efficient and meaningful manner. In terms of audio data, the first challenge has traditionally been the realm of audio compression research that has focused on statistical, unstructured audio representations that obfuscate the inherent structure and semantic content of the underlying data. This has only served to further complicate the resolution of the second challenge resulting in access mechanisms that are either impractical to implement, too inflexible for general application or too low level for the average user. Thus, an artificial dichotomy has been created from what is in essence a dual problem. The founding motivation of this thesis is that, although the hypermedia model has been identified as the ideal, cognitively justified method for organising data, existing audio data representations and coding models provide little, if any, support for, or resemblance to, this model. It is the contention of the author that any successful attempt to create hyperaudio must resolve this schism, addressing both storage and information management issues simultaneously. In order to achieve this aim, an audio representation must be designed that provides compact data storage while, at the same time, revealing the inherent structure of the underlying data. Thus it is the aim of this thesis to present a representation designed with these factors in mind. Perhaps the most difficult hurdle in the way of achieving the aims of content-based audio coding and information management is that of auditory source separation. The MPEG committee has noted this requirement during the development of its MPEG-7 standard, however, the mechanics of "how" to achieve auditory source separation were left as an open research question. This same committee proposed that MPEG-7 would "support descriptors that can act as handles referring directly to the data, to allow manipulation of the multimedia material." While meta-data tags are a part solution to this problem, these cannot allow manipulation of audio material down to the level of individual sources when several simultaneous sources exist in a recording. In order to achieve this aim, the data themselves must be encoded in such a manner that allows these descriptors to be formed. Thus, content-based coding is obviously required. In the case of audio, this is impossible to achieve without effecting auditory source separation. Auditory source separation is the concern of computational auditory scene analysis (CASA). However, the findings of CASA research have traditionally been restricted to a limited domain. To date, the only real application of CASA research to what could loosely be classified as information management has been in the area of signal enhancement for automatic speech recognition systems. In these systems, a CASA front end serves as a means of separating the target speech from the background "noise". As such, the design of a CASA-based approach, as presented in this thesis, to one of the most significant challenges facing audio information management research represents a significant contribution to the field of information management. Thus, this thesis unifies research from three distinct fields in an attempt to resolve some specific and general challenges faced by all three. It describes an audio representation that is based on a sinusoidal model from which low-level auditory primitive elements are extracted. The use of a sinusoidal representation is somewhat contentious with the modern trend in CASA research tending toward more complex approaches in order to resolve issues relating to co-incident partials. However, the choice of a sinusoidal representation has been validated by the demonstration of a method to resolve many of these issues. The majority of the thesis contributes several algorithms to organise the low-level primitives into low-level auditory objects that may form the basis of nodes or link anchor points in a hyperaudio structure. Finally, preliminary investigations in the representation’s suitability for coding and information management tasks are outlined as directions for future research.

Hearing aid devices are used to help people with hearing impairment. The number of people that requires hearingaid devices are possibly constant over the years, however the number of people that now have access to hearing aiddevices increasing rapidly. The hearing aid devices must be small, consume very little power, and be fairly accurate.Even though it is normally more important for the user that hearing impairment look good (are discrete). Once thehearing aid device prescribed to the user, she/he needs to train and adjust the device to compensate for the individualimpairment.We are within the framework of this project researching on hearing aid devices that can be trained by the hearingimpaired person her-/himself. This project is about finding suitable noise cancellation algorithm for the hearing-aiddevice. We consider several types of algorithms like, microphone array signal processing, Independent ComponentAnalysis (ICA) based on double microphone called Blind Source Separation (BSS) and DRNPE algorithm.We run this current and most sophisticated and robust algorithms in certain noise backgrounds like Cocktail noise,street, public places, train, babble situations to test the efficiency. The BSS algorithm was well in some situation andgave average results in some situations. Where one microphone gave steady results in all situations. The output isgood enough to listen targeted audio.The functionality and performance of the proposed algorithm is evaluated with different non-stationary noisebackgrounds. From the performance results it can be concluded that, by using the proposed algorithm we are able toreduce the noise to certain level. SNR, system delay, minimum error and audio perception are the vital parametersconsidered to evaluate the performance of algorithms. Based on these parameters an algorithm is suggested forheairng-aid. / Hearing-Aid

Thesis (Ph. D.)--Michigan State University. Dept. of Physics, 2008. / Title from PDF t.p. (viewed on July 22, 2009) Includes bibliographical references (p. 236-243). Also issued in print.