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Micro-speakers based on the electro-dynamical transduction principle show a particular transfer behavior, which cannot be described by conventional models developed for loudspeakers and headphones. This paper presents an advanced lumped parameter model, which considers dominant nonlinearities, time variance, visco-elastic behavior at low frequencies, modal vibration and sound radiation at high frequencies. The relevance of the new model parameters for the design and evaluation of micro-speakers and other transducers are discussed.
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The aspects of what provides a good user experience with headphones is initially investigated by an exploratory study (experiment I). Using KJ-Technique, 5 workshop teams of 4-6 participants each provide a number of aspects influencing their experience with headphones. Analysing the aspects for uniqueness and relatedness provides 144 aspects of user experience with headphones, arranged in 12 categories. The 144 influencing aspects from experiment I are condensed, and 24 attributes regarding user experience with headphones are selected. These attributes are tested in regard to their correlation with and effects on overall evaluation of headphones in a second experiment, thus investigating which attributes are most influential for user experience. Using a within-subject design, eight different headphones are evaluated according to the attributes along with an overall evaluation. The attributes are listed in the following categories: sound quality, comfort, build quality, design and brand. A factor analysis shows that the categories fit the attributes. Furthermore, some attributes show high correlations with the overall evaluation, suggesting that these attributes are important for user experience with headphones. The highest rated attributes are shape, design, quality of contact surfaces, comfort, goodness of fit and build quality. An interpretation of which attributes are the most influential in relation to user experience with headphones is discussed.
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Modern mobile virtual reality headsets present an opportunity to display live panoramic video and 3D audio content. This paper describes a recent real-world case study for a live streaming framework in which a concert of the Berlin Philharmonic Orchestra was streamed in panoramic video and 3D audio to virtual reality headsets on site, as well as to the web.
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Electro Magnetic Interference (EMI) performance is, other than electro acoustic performance, one of the most important aspects of designing headsets specifically for cellular phones and other portable handset applications. A system to measure the EMI performance of headsets was studied, built and tested with almost two dozen headsets. The results of tests show that the differences of cabling methods greatly influenced both EMI and crosstalk performance. The impact of different cable shielding conditions was simulated and is documented herein
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This paper documents the development of a miniature programmable completely-in-the-canal hearing aid (“active earplug”) aimed as a tool for auditory neuroscience research. The main motivation of this project is to provide researchers with the ability to chronically change chosen aspects of the auditory experience in animals or human subjects. The active earplug is designed around a compact system-on-a-chip package (Belasigna 300, ON Semiconductors, Phoenix, USA) comprising digital converters, preamplifiers and a DSP processor. This chip interfaces with miniature receiver and microphone (Knowles, Itasca, IL, USA) with minimal supporting circuitry. The active earplug is designed to be custom-fitted in each subject’s ear canal using a silicone mold. Arbitrary signal processing algorithms can be implemented on the DSP, therefore modifications of the acoustic inputs of the ear with an earplug can be chronically tested. This active earplug will enable researchers to study the effects of chronic expose to arbitrary signal degradations or augmentations, including hearing aid algorithms.
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Head-related transfer function (HRTF) is essential to realize an immersive listening experience over headphones, which is unique for every individual. Conventionally, HRTFs are measured using discrete stop-and-go method for multiple loudspeaker positions, which is a tedious and time consuming process, especially for human subjects. Recently, continuous HRTF acquisition methods have been proposed to improve the acquisition efficiency. However, these methods still require constrained or limited movements of subjects and can only be used in a controlled environment. In this paper, we present a novel fast and continuous HRTF acquisition system that incorporates head-tracker to allow unconstrained head movements in azimuth and elevation. An improved adaptive filtering approach that combines conventional progressive based normalized least mean square algorithm (NLMS) and previously proposed activated based NLMS is proposed to extract HRTFs on-the-fly from such binaural measurements with random head movements in both azimuth and elevation. Experimental results demonstrate that the proposed approach significantly enhances the performance of conventional progressive NLMS for short duration measurements and further validates the accuracy of proposed HRTF acquisition method.
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In binaural simulations, Head-Related Impulse Responses are used to recreate a 3D auditory display through headphones. Public repositories of individually measured HRIRs are widely used in industry and research. However, head-related anthropometric asymmetries, among measured subjects, are a likely cause of measured asymmetries in Interaural Time Delay cues (ITDs), which may lead to imprecise sound localization. As part of a larger study on HRIR personalization, this paper expands, to the elevation dimension, the investigation of ITD asymmetry in public databases of measured HRIRs. In a previous exploratory study, concerning the horizontal plane only, a region of sensitivity, where the ITD asymmetry was observed to be significantly more prominent, was identified in datasets of individually measured HRIRs approximately between the azimuth range of θ = ±90° to ±130°. For this paper. two publicly available databases of individual HRIRs were selected and analyzed in search of an elevation effect on ITD symmetry. Results found that an increase or decrease in elevation angle φ , away from the horizontal plane, affects the asymmetry curve by reducing the gap between average and peak ITD asymmetry values within the mentioned region in a roughly linear trend. This finding points to the fact that, within the examined datasets, the statistical presence of ITD asymmetries is gradually less severe, although still present, as the elevation angle moves away from the horizontal plane.
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With the recent development of low-cost and efficient methods for generating individualized Interaural Time Differences (ITDs), this paper investigates the distribution of interaural distances among certain populations in order provide a framework for improving the performance of individualized binaural audio systems across a wider range of head morphologies. Interaural distances are extracted from the publicly available LISTEN and CIPIC spatial audio databases in order to generate distributions across subjects, and from the MARL-NYU database in order to investigate measurement stability across testing sessions. The interaural difference is shown to be a means to measure the magnitude of an individual’s set of ITDs. Furthermore, the constraints introduced on the precision of measured ITDs by limited sampling rates across all three datasets are explored, and the authors motivate the use of higher sampling rates in the development of spatial audio databases.
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Individualized head-related transfer functions (HRTFs) are closely related to anthropometry (measurements of torso, head, and pinna) of listeners. This relation not only derives the individualized HRTFs from anthropometric measurements, but can also be viewed as a means to derive the anthropometry of the listener from his/her measured HRTFs (bypass direct anthropometric measurements). In this study, we propose to estimate a person’s anthropometry information using the linear representation obtained from the individualized HRTF features of the person and a HRTF feature database with a number of subjects. Five different HRTF features as well as their best combination are considered in the training stage. Although our experiments showed that the performance of these methods varies in general, the best combination method yields considerable accuracy for the estimation of most anthropometric features. The proposed idea also provides further insights on the complex relation between anthropometry and HRTFs. Our experiment revealed that the anthropometric features that are not well estimated could be removed from HRTF individualization process without causing significant performance degradation.
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A natural integration of virtual sound sources with the real environment soundscape using a natural augmented reality (NAR) headset is discussed in this paper. These NAR headsets consist of dual sensing microphones at each earcup and employ adaptive filtering technique to achieve natural listening in augmented reality applications. We propose an adaptive equalization of the open-back NAR headsets using non-stationary virtual signals to compensate for individualized headphones transfer function (HPTF) and acoustic coupling to seamlessly mix virtual sound with the environmental sound. Training of the NAR headsets are carried out using fast-converging normalized filtered-x least mean square algorithms to respond to changing sound variation. Significant changes in HPTF can be detected online and fast HPTF estimation using normalized least mean square algorithm is employed to update the secondary path estimates.
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