491 research outputs found

    The CogniAid trial. The impact of two hearing aid signal processing strategies on cognition

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    BackgroundUntreated hearing loss is a risk factor for age-related cognitive decline and hearing aids have been shown to slow cognitive decline in a population at risk for dementia. This double-blind multiple site randomized trial tested the hypothesis that for older adults with below-average cognition, a “Simple” hearing aid fitting strategy (based on linear amplification with output limiting compression signal processing) would improve hearing and cognition more than a “Standard” approach (adaptive compression-based processing).MethodsTwo hundred and fifty-six adults aged over 65 were screened for cognitive function using the NIH toolbox cognitive battery. Participants with below median age-adjusted fluid composite cognitive scores (<100) were eligible to participate (n = 104). Sixty-seven eligible participants proceeded to trial and were randomized 1:1 to a simple or standard hearing aid fitting. Participants in the Standard group were fitted with hearing aids matched to non-linear real-ear prescription targets (either NAL-NL1 or NL2), while participants in the Simple group were fitted with hearing aids matched to linear prescription targets (NAL-R). Participants and researchers not fitting the hearing aids were blinded to allocation.ResultsForty-eight participants completed assessments in 12 months. The Standard hearing aid group improved on measures of fluid cognition and hearing. There was a statistically significant difference in fluid cognition scores between groups. The fluid cognition composite score for participants receiving the Simple fitting changed by 3.5 points. Those with the Standard fitting improved by 10.3 points. Hearing outcomes for each group were improved by the same amount.ConclusionThis is the first study to show that hearing aid fitting strategies using markedly different signal processing result in significantly different cognitive outcomes after 12 months of use. The Standard fitting resulted in greater improvement in cognition than the Simpler fitting which was the opposite result to what had been hypothesized. The results reinforce findings indicating hearing aid benefits for the elderly and that they improve cognition

    Iceberg: a loudspeaker-based room auralization method for auditory research

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    Depending on the acoustic scenario, people with hearing loss are challenged on a different scale than normal hearing people to comprehend sound, especially speech. That happen especially during social interactions within a group, which often occurs in environments with low signal-to-noise ratios. This communication disruption can create a barrier for people to acquire and develop communication skills as a child or to interact with society as an adult. Hearing loss compensation aims to provide an opportunity to restore the auditory part of socialization. Technology and academic efforts progressed to a better understanding of the human hearing system. Through constant efforts to present new algorithms, miniaturization, and new materials, constantly-improving hardware with high-end software is being developed with new features and solutions to broad and specific auditory challenges. The effort to deliver innovative solutions to the complex phenomena of hearing loss encompasses tests, verifications, and validation in various forms. As the newer devices achieve their purpose, the tests need to increase the sensitivity, requiring conditions that effectively assess their improvements. Regarding realism, many levels are required in hearing research, from pure tone assessment in small soundproof booths to hundreds of loudspeakers combined with visual stimuli through projectors or head-mounted displays, light, and movement control. Hearing aids research commonly relies on loudspeaker setups to reproduce sound sources. In addition, auditory research can use well-known auralization techniques to generate sound signals. These signals can be encoded to carry more than sound pressure level information, adding spatial information about the environment where that sound event happened or was simulated. This work reviews physical acoustics, virtualization, and auralization concepts and their uses in listening effort research. This knowledge, combined with the experiments executed during the studies, aimed to provide a hybrid auralization method to be virtualized in four-loudspeaker setups. Auralization methods are techniques used to encode spatial information into sounds. The main methods were discussed and derived, observing their spatial sound characteristics and trade-offs to be used in auditory tests with one or two participants. Two well-known auralization techniques (Ambisonics and Vector-Based Amplitude Panning) were selected and compared through a calibrated virtualization setup regarding spatial distortions in the binaural cues. The choice of techniques was based on the need for loudspeakers, although a small number of them. Furthermore, the spatial cues were examined by adding a second listener to the virtualized sound field. The outcome reinforced the literature around spatial localization and these techniques driving Ambisonics to be less spatially accurate but with greater immersion than Vector-Based Amplitude Panning. A combination study to observe changes in listening effort due to different signal-to-noise ratios and reverberation in a virtualized setup was defined. This experiment aimed to produce the correct sound field via a virtualized setup and assess listening effort via subjective impression with a questionnaire, an objective physiological outcome from EEG, and behavioral performance on word recognition. Nine levels of degradation were imposed on speech signals over speech maskers separated in the virtualized space through Ambisonics' first-order technique in a setup with 24 loudspeakers. A high correlation between participants' performance and their responses on the questionnaire was observed. The results showed that the increased virtualized reverberation time negatively impacts speech intelligibility and listening effort. A new hybrid auralization method was proposed merging the investigated techniques that presented complementary spatial sound features. The method was derived through room acoustics concepts and a specific objective parameter derived from the room impulse response called Center Time. The verification around the binaural cues was driven with three different rooms (simulated). As the validation with test subjects was not possible due to the COVID-19 pandemic situation, a psychoacoustic model was implemented to estimate the spatial accuracy of the method within a four-loudspeaker setup. Also, an investigation ran the same verification, and the model estimation was performed with the introduction of hearing aids. The results showed that it is possible to consider the hybrid method with four loudspeakers for audiological tests while considering some limitations. The setup can provide binaural cues to a maximum ambiguity angle of 30 degrees in the horizontal plane for a centered listener

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Real-world listening effort in adult cochlear implant users

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    Cochlear implants (CI) are a treatment to provide a sense of hearing to individuals with severe-to-profound sensorineural hearing loss. Even when optimal levels of intelligibility are achieved after cochlear implantation, many CI users complain about the effort required to understand speech in everyday life contexts. This sustained mental exertion, commonly known as “listening effort”, could negatively affect their lives, especially regarding communication, participation, and long-term cognitive health. This thesis aimed to evaluate the listening effort experienced by CI recipients in real-world sound scenarios. The research focused on social listening situations that are particularly common in everyday life such as having conversations in a busy café or communicating through video call. Additionally, some situations that prevailed during the COVID-19 pandemic were also examined (e.g., listening to someone who is wearing a facemask). Multimodal measures of listening effort were employed throughout the research project to obtain a comprehensive assessment. Nonetheless, the primary focus was on measures that quantify objectively the cognitive demands of listening through a CI. To that end, we used a combination of physiological measures, functional near infrared spectroscopy (fNIRS) brain imaging and simultaneous pupillometry, both of which are compatible with CIs and capable of providing insights into the neural underpinnings of effortful listening. We also proposed a novel approach to quantify “listening efficiency”, an integrated behavioural measure that reflects both intelligibility and listening effort. We successfully applied these assessments to 168 CI users and 75 age-matched normally hearing (NH) controls who were recruited throughout the project. We found that CI users experienced high levels of listening effort, even when their intelligibility was optimal under highly favourable listening conditions. Objective measures revealed that CI listeners exhibited significantly inferior listening efficiency than NH controls when listening to speech under moderate levels of cafeteria background noise and when attending online video calls. Physiologically, they showed elevated levels of arousal as revealed by larger and prolonged pupil dilations to baseline compared with NH controls, suggesting high cognitive load and increased need for recovery. The importance of visual cues was evident; the presence of video and captions benefited CI recipients by improving considerably their listening efficiency during online communication. These results were consistent with their subjective ratings of effort, both in the experiments and in daily life. These findings provide objective evidence of the cognitive burden endured by CI listeners in everyday life. In addition, the objective assessments proposed were proved feasible to quantify the performance and cognitive demands of listening through a CI. In particular, listening efficiency showed sensitivity to differences in task demands and between groups, even when intelligibility remained near perfect. We argue that listening efficiency holds potential to become a CI outcome measure

    Literacy for digital futures : Mind, body, text

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    The unprecedented rate of global, technological, and societal change calls for a radical, new understanding of literacy. This book offers a nuanced framework for making sense of literacy by addressing knowledge as contextualised, embodied, multimodal, and digitally mediated. In today’s world of technological breakthroughs, social shifts, and rapid changes to the educational landscape, literacy can no longer be understood through established curriculum and static text structures. To prepare teachers, scholars, and researchers for the digital future, the book is organised around three themes – Mind and Materiality; Body and Senses; and Texts and Digital Semiotics – to shape readers’ understanding of literacy. Opening up new interdisciplinary themes, Mills, Unsworth, and Scholes confront emerging issues for next-generation digital literacy practices. The volume helps new and established researchers rethink dynamic changes in the materiality of texts and their implications for the mind and body, and features recommendations for educational and professional practice

    Antennas and Electromagnetics Research via Natural Language Processing.

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    Advanced techniques for performing natural language processing (NLP) are being utilised to devise a pioneering methodology for collecting and analysing data derived from scientific literature. Despite significant advancements in automated database generation and analysis within the domains of material chemistry and physics, the implementation of NLP techniques in the realms of metamaterial discovery, antenna design, and wireless communications remains at its early stages. This thesis proposes several novel approaches to advance research in material science. Firstly, an NLP method has been developed to automatically extract keywords from large-scale unstructured texts in the area of metamaterial research. This enables the uncovering of trends and relationships between keywords, facilitating the establishment of future research directions. Additionally, a trained neural network model based on the encoder-decoder Long Short-Term Memory (LSTM) architecture has been developed to predict future research directions and provide insights into the influence of metamaterials research. This model lays the groundwork for developing a research roadmap of metamaterials. Furthermore, a novel weighting system has been designed to evaluate article attributes in antenna and propagation research, enabling more accurate assessments of impact of each scientific publication. This approach goes beyond conventional numeric metrics to produce more meaningful predictions. Secondly, a framework has been proposed to leverage text summarisation, one of the primary NLP tasks, to enhance the quality of scientific reviews. It has been applied to review recent development of antennas and propagation for body-centric wireless communications, and the validation has been made available for comparison with well-referenced datasets for text summarisation. Lastly, the effectiveness of automated database building in the domain of tunable materials and their properties has been presented. The collected database will use as an input for training a surrogate machine learning model in an iterative active learning cycle. This model will be utilised to facilitate high-throughput material processing, with the ultimate goal of discovering novel materials exhibiting high tunability. The approaches proposed in this thesis will help to accelerate the discovery of new materials and enhance their applications in antennas, which has the potential to transform electromagnetic material research

    Acoustic modelling, data augmentation and feature extraction for in-pipe machine learning applications

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    Gathering measurements from infrastructure, private premises, and harsh environments can be difficult and expensive. From this perspective, the development of new machine learning algorithms is strongly affected by the availability of training and test data. We focus on audio archives for in-pipe events. Although several examples of pipe-related applications can be found in the literature, datasets of audio/vibration recordings are much scarcer, and the only references found relate to leakage detection and characterisation. Therefore, this work proposes a methodology to relieve the burden of data collection for acoustic events in deployed pipes. The aim is to maximise the yield of small sets of real recordings and demonstrate how to extract effective features for machine learning. The methodology developed requires the preliminary creation of a soundbank of audio samples gathered with simple weak annotations. For practical reasons, the case study is given by a range of appliances, fittings, and fixtures connected to pipes in domestic environments. The source recordings are low-reverberated audio signals enhanced through a bespoke spectral filter and containing the desired audio fingerprints. The soundbank is then processed to create an arbitrary number of synthetic augmented observations. The data augmentation improves the quality and the quantity of the metadata and automatically creates strong and accurate annotations that are both machine and human-readable. Besides, the implemented processing chain allows precise control of properties such as signal-to-noise ratio, duration of the events, and the number of overlapping events. The inter-class variability is expanded by recombining source audio blocks and adding simulated artificial reverberation obtained through an acoustic model developed for the purpose. Finally, the dataset is synthesised to guarantee separability and balance. A few signal representations are optimised to maximise the classification performance, and the results are reported as a benchmark for future developments. The contribution to the existing knowledge concerns several aspects of the processing chain implemented. A novel quasi-analytic acoustic model is introduced to simulate in-pipe reverberations, adopting a three-layer architecture particularly convenient for batch processing. The first layer includes two algorithms: one for the numerical calculation of the axial wavenumbers and one for the separation of the modes. The latter, in particular, provides a workaround for a problem not explicitly treated in the literature and related to the modal non-orthogonality given by the solid-liquid interface in the analysed domain. A set of results for different waveguides is reported to compare the dispersive behaviour against different mechanical configurations. Two more novel solutions are also included in the second layer of the model and concern the integration of the acoustic sources. Specifically, the amplitudes of the non-orthogonal modal potentials are obtained using either a distance minimisation objective function or by solving an analytical decoupling problem. In both cases, results show that sources sufficiently smooth can be approximated with a limited number of modes keeping the error below 1%. The last layer proposes a bespoke approach for the integration of the acoustic model into the synthesiser as a reverberation simulator. Additional elements of novelty relate to the other blocks of the audio synthesiser. The statistical spectral filter, for instance, is a batch-processing solution for the attenuation of the background noise of the source recordings. The signal-to-noise ratio analysis for both moderate and high noise levels indicates a clear improvement of several decibels against the closest filter example in the literature. The recombination of the audio blocks and the system of fully tracked annotations are also novel extensions of similar approaches recently adopted in other contexts. Moreover, a bespoke synthesis strategy is proposed to guarantee separable and balanced datasets. The last contribution concerns the extraction of convenient sets of audio features. Elements of novelty are introduced for the optimisation of the filter banks of the mel-frequency cepstral coefficients and the scattering wavelet transform. In particular, compared to the respective standard definitions, the average F-score performance of the optimised features is roughly 6% higher in the first case and 2.5% higher for the latter. Finally, the soundbank, the synthetic dataset, and the fundamental blocks of the software library developed are publicly available for further research

    2023/2024 University of the Pacific Stockton General Catalog

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    A review of auditory processing and cognitive change during normal ageing, and the implications for setting hearing aids for older adults

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    Throughout our adult lives there is a decline in peripheral hearing, auditory processing and elements of cognition that support listening ability. Audiometry provides no information about the status of auditory processing and cognition, and older adults often struggle with complex listening situations, such as speech in noise perception, even if their peripheral hearing appears normal. Hearing aids can address some aspects of peripheral hearing impairment and improve signal-to-noise ratios. However, they cannot directly enhance central processes and may introduce distortion to sound that might act to undermine listening ability. This review paper highlights the need to consider the distortion introduced by hearing aids, specifically when considering normally-ageing older adults. We focus on patients with age-related hearing loss because they represent the vast majority of the population attending audiology clinics. We believe that it is important to recognize that the combination of peripheral and central, auditory and cognitive decline make older adults some of the most complex patients seen in audiology services, so they should not be treated as “standard” despite the high prevalence of age-related hearing loss. We argue that a primary concern should be to avoid hearing aid settings that introduce distortion to speech envelope cues, which is not a new concept. The primary cause of distortion is the speed and range of change to hearing aid amplification (i.e., compression). We argue that slow-acting compression should be considered as a default for some users and that other advanced features should be reconsidered as they may also introduce distortion that some users may not be able to tolerate. We discuss how this can be incorporated into a pragmatic approach to hearing aid fitting that does not require increased loading on audiology services
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