438 research outputs found

    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

    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

    Music Production Behaviour Modelling

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    The new millennium has seen an explosion of computational approaches to the study of music production, due in part to the decreasing cost of computation and the increase of digital music production techniques. The rise of digital recording equipment, MIDI, digital audio workstations (DAWs), and software plugins for audio effects led to the digital capture of various processes in music production. This discretization of traditionally analogue methods allowed for the development of intelligent music production, which uses machine learning to numerically characterize and automate portions of the music production process. One algorithm from the field referred to as ``reverse engineering a multitrack mix'' can recover the audio effects processing used to transform a multitrack recording into a mixdown in the absence of information about how the mixdown was achieved. This thesis improves on this method of reverse engineering a mix by leveraging recent advancements in machine learning for audio. Using the differentiable digital signal processing paradigm, greybox modules for gain, panning, equalisation, artificial reverberation, memoryless waveshaping distortion, and dynamic range compression are presented. These modules are then connected in a mixing chain and are optimized to learn the effects used in a given mixdown. Both objective and perceptual metrics are presented to measure the performance of these various modules in isolation and within a full mixing chain. Ultimately a fully differentiable mixing chain is presented that outperforms previously proposed methods to reverse engineer a mix. Directions for future work are proposed to improve characterization of multitrack mixing behaviours

    Changing Priorities. 3rd VIBRArch

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    In order to warrant a good present and future for people around the planet and to safe the care of the planet itself, research in architecture has to release all its potential. Therefore, the aims of the 3rd Valencia International Biennial of Research in Architecture are: - To focus on the most relevant needs of humanity and the planet and what architectural research can do for solving them. - To assess the evolution of architectural research in traditionally matters of interest and the current state of these popular and widespread topics. - To deepen in the current state and findings of architectural research on subjects akin to post-capitalism and frequently related to equal opportunities and the universal right to personal development and happiness. - To showcase all kinds of research related to the new and holistic concept of sustainability and to climate emergency. - To place in the spotlight those ongoing works or available proposals developed by architectural researchers in order to combat the effects of the COVID-19 pandemic. - To underline the capacity of architectural research to develop resiliency and abilities to adapt itself to changing priorities. - To highlight architecture's multidisciplinarity as a melting pot of multiple approaches, points of view and expertise. - To open new perspectives for architectural research by promoting the development of multidisciplinary and inter-university networks and research groups. For all that, the 3rd Valencia International Biennial of Research in Architecture is open not only to architects, but also for any academic, practitioner, professional or student with a determination to develop research in architecture or neighboring fields.Cabrera Fausto, I. (2023). Changing Priorities. 3rd VIBRArch. Editorial Universitat Politècnica de València. https://doi.org/10.4995/VIBRArch2022.2022.1686

    Risk Exposure to Particles – including Legionella pneumophila – emitted during Showering with Water-Saving Showers

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    The increase in legionellosis incidence in the general population in recent years calls for a better characterization of the sources of infection, such as showering. Water-efficient shower systems that use water atomization technology may emit slightly more inhalable bacteria-sized particles than traditional systems, which may increase the risk of users inhaling contaminants associated with these water droplets. To evaluate the risk, the number and mass of inhalable water droplets emitted by twelve showerheads—eight using water-atomization technology and four using continuous-flow technology— were monitored in a shower stall. The water-atomizing showers tested not only had lower flow rates, but also larger spray angles, less nozzles, and larger nozzle diameters than those of the continuous-flow showerheads. A difference in the behavior of inhalable water droplets between the two technologies was observed, both unobstructed or in the presence of a mannequin. The evaporation of inhalable water droplets emitted by the water-atomization showers favored a homogenous distribution in the shower stall. In the presence of the mannequin, the number and mass of inhalable droplets increased for the continuous-flow showerheads and decreased for the water-atomization showerheads. The water-atomization showerheads emitted less inhalable water mass than the continuous-flow showerheads did per unit of time; however, they generally emitted a slightly higher number of inhalable droplets—only one model performed as well as the continuous-flow showerheads in this regard. To specifically assess the aerosolisation rate of bacteria, in particular of the opportunistic water pathogen Legionella pneumophila, during showering controlled experiments were run with one atomization showerhead and one continuous-flow, first inside a glove box, second inside a shower stall. The bioaerosols were sampled with a Coriolis® air sampler and the total number of viable (cultivable and noncultivable) bacteria was determined by flow cytometry and culture. We found that the rate of viable and cultivable Legionella aerosolized from the water jet was similar between the two showerheads: the viable fraction represents 0.02% of the overall bacteria present in water, while the cultivable fraction corresponds to only 0.0005%. The two showerhead models emitted a similar ratio of airborne Legionella viable and cultivable per volume of water used. Similar results were obtained with naturally contaminated hoses tested in shower stall. Therefore, the risk of exposure to Legionella is not expected to increase significantly with the new generation of water-efficient showerheads

    The influence of vision on the perceptual compensation for reverberation in simulated environments

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    In typical listening environments, auditory signals arrive at the ear as a fusion of the direct energy from sound sources and the indirect reflections via reverberation. The listener thus cannot directly access the source and reverberation components individually, highlighting that the perceptual separation of these components can be subject to ambiguity. Accurate expectations of reverberation have been shown to reduce such ambiguity. The visible features of the physical environment (e.g., spatial and surface properties) can reveal aspects of reverberation that inform such expectations, suggesting an inferential role of vision in disambiguating the source and reverberation components. The aim of this thesis was to evaluate the degree to which visual information from simulated environments can affect the expectations of reverberation to consequently improve judgements of sound sources. To investigate this aim, we conducted three behavioural studies that assessed perception in audiovisual environments via online simulations created from a database of real-world locations. Chapter 3 assessed whether visual cues to the environment could inform of the reverberant properties of physical locations in an audiovisual congruence task. The results indicated a greater impression of congruence when reverberant cues were identical or similar to those represented by the depicted environment, demonstrating a capacity for vision to inform meaningful expectations of reverberation. Chapter 4 evaluated the degree to which vision contributed to the identification of speech sources within reverberation by prior exposure to visual environments. We found that exposure to the visual environment had hardly any effect on improving the identification of reverberant speech sources in this context. Chapter 5 investigated if a concurrent visual depiction of the environment would affect the tendency for estimates of sound source duration to be consistent despite varying reverberation. The results showed that source duration estimates were influenced by the degree of reverberation present, and were seemingly unaffected by any visual exposure. Taken together, the findings of this thesis suggest that scene understanding from vision contributes to the overall spatial understanding of environments and their reverberant properties, but appears to contribute little to enhancing the perceptual separation of source and reverberation components used to improve judgements of auditory sources

    Exploring Animal Behavior Through Sound: Volume 1

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    This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government

    Data-driven Speech Intelligibility Enhancement and Prediction for Hearing Aids

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    Hearing impairment is a widespread problem around the world. It is estimated that one in six people are living with some degree of hearing loss. Moderate and severe hearing impairment has been recognised as one of the major causes of disability, which is associated with declines in the quality of life, mental illness and dementia. However, investigation shows that only 10-20\% of older people with significant hearing impairment wear hearing aids. One of the main factors causing the low uptake is that current devices struggle to help hearing aid users understand speech in noisy environments. For the purpose of compensating for the elevated hearing thresholds and dysfunction of source separation processing caused by the impaired auditory system, amplification and denoising have been the major focuses of current hearing aid studies to improve the intelligibility of speech in noise. Also, it is important to derive a metric that can fairly predict speech intelligibility for the better development of hearing aid techniques. This thesis aims to enhance the speech intelligibility of hearing impaired listeners. Motivated by the success of data-driven approaches in many speech processing applications, this work proposes the differentiable hearing aid speech processing (DHASP) framework to optimise both the amplification and denoising modules within a hearing aid processor. This is accomplished by setting an intelligibility-based optimisation objective and taking advantage of large-scale speech databases to train the hearing aid processor to maximise the intelligibility for the listeners. The first set of experiments is conducted on both clean and noisy speech databases, and the results from objective evaluation suggest that the amplification fittings optimised within the DHASP framework can outperform a widely used and well-recognised fitting. The second set of experiments is conducted on a large-scale database with simulated domestic noisy scenes. The results from both objective and subjective evaluations show that the DHASP-optimised hearing aid processor incorporating a deep neural network-based denoising module can achieve competitive performance in terms of intelligibility enhancement. A precise intelligibility predictor can provide reliable evaluation results to save the cost of expensive and time-consuming subjective evaluation. Inspired by the findings that automatic speech recognition (ASR) models show similar recognition results as humans in some experiments, this work exploits ASR models for intelligibility prediction. An intrusive approach using ASR hidden representations and a non-intrusive approach using ASR uncertainty are proposed and explained in the third and fourth experimental chapters. Experiments are conducted on two databases, one with monaural speech in speech-spectrum-shaped noise with normal hearing listeners, and the other one with processed binaural speech in domestic noise with hearing impaired listeners. Results suggest that both the intrusive and non-intrusive approaches can achieve top performances and outperform a number of widely used intelligibility prediction approaches. In conclusion, this thesis covers both the enhancement and prediction of speech intelligibility for hearing aids. The proposed hearing aid processor optimised within the proposed DHASP framework can significantly improve the intelligibility of speech in noise for hearing impaired listeners. Also, it is shown that the proposed ASR-based intelligibility prediction approaches can achieve state-of-the-art performances against a number of widely used intelligibility predictors

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
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