Bulk download - click topic to download Zip archive of all papers related to that topic: Applications in audio Architectural Acoustics Audio and Education Audio quality Audio Signal Processing Evaluation of spatial audio Forensic audio Listening tests and case-studies Multichannel and spatial audio processing and applications Spatial audio applications Spatial audio applicatons Transducers
This work introduces an Open Source turntable for the measurement of electro-acoustical devices. The idea is to provide an inexpensive and highly customizable device that can be adjusted according to specific measurement needs. Development of such turntable devices in the past required significant i n vestment. Specific mechanical and motor control design skills were needed, leading to both costly and time-consuming processes. Recent developments in mechatronics and 3D printing allow to design and build a cost-effective solution.
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This work introduces an Open Source turntable for the measurement of electro-acoustical devices. The idea is to provide an inexpensive and highly customizable device that can be adjusted according to specific measurement needs. Development of such turntable devices in the past required significant i n vestment. Specific mechanical and motor control design skills were needed, leading to both costly and time-consuming processes. Recent developments in mechatronics and 3D printing allow to design and build a cost-effective solution.
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A method for recreating complex soundscapes for tasks related to audio quality evaluation is presented. This approach uses an ambisonics-inspired basis for recreating dynamic noise in a system compatible with ETSI standard EG 202 396-1 for background noise reproduction. Recordings were captured with a spherical 32-microphone array and processed to match the two-dimensional four-loudspeaker array by creating four directional beams, each feeding an individual channel. As a result, a spatial background noise ambience is recreated, preserving the transient characteristics of the original recording.
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A method for recreating complex soundscapes for tasks related to audio quality evaluation is presented. This approach uses an ambisonics-inspired basis for recreating dynamic noise in a system compatible with ETSI standard EG 202 396-1 for background noise reproduction. Recordings were captured with a spherical 32-microphone array and processed to match the two-dimensional four-loudspeaker array by creating four directional beams, each feeding an individual channel. As a result, a spatial background noise ambience is recreated, preserving the transient characteristics of the original recording.
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The ability to generate appropriate auditory localization cues is an important requisite of spatial audio rendering technology that contributes to the plausibility of virtual sounds presented to a user, especially in XR applications (VR/AR/MR). Algorithmic approaches have been proposed to quantify such technologies’ ability to reproduce interaural level difference (ILD) cues through regression and statistical methods, providing a useful standardization and automation method to estimate the localization accuracy potential of a given spatial audio rendering engine. Previous approaches are extended to include interaural time difference (ITD) cues as part the perceptual transform through the use of the interaural transfer function (ITF). The extended algorithmic approach of quantifying localization accuracy may provide an adequate substitute for critical listening studies as an evaluation method. However, this approach has not yet been validated through comparison with localization listening studies. A review of listening tests are reviewed in conclusion to increase confidence in presented methods of algorithmically quantifying localization accuracy potential of a spatial audio rendering engine.
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The ability to generate appropriate auditory localization cues is an important requisite of spatial audio rendering technology that contributes to the plausibility of virtual sounds presented to a user, especially in XR applications (VR/AR/MR). Algorithmic approaches have been proposed to quantify such technologies’ ability to reproduce interaural level difference (ILD) cues through regression and statistical methods, providing a useful standardization and automation method to estimate the localization accuracy potential of a given spatial audio rendering engine. Previous approaches are extended to include interaural time difference (ITD) cues as part the perceptual transform through the use of the interaural transfer function (ITF). The extended algorithmic approach of quantifying localization accuracy may provide an adequate substitute for critical listening studies as an evaluation method. However, this approach has not yet been validated through comparison with localization listening studies. A review of listening tests are reviewed in conclusion to increase confidence in presented methods of algorithmically quantifying localization accuracy potential of a spatial audio rendering engine.
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MPEG-H Audio is a Next Generation Audio (NGA) system offering a new audio experience for various applications: Object-based immersive sound delivers a new degree of realism and artistic freedom for immersive music applications, such as the 360 Reality Audio music service. Advanced interactivity options enable improved personalization and accessibility. Solutions exist, to create object-based features from legacy material, e.g., deep-learning-based dialogue enhancement. 'Universal delivery' allows for optimal rendering of a production over all kinds of devices and various ways of distribution like broadcast or streaming. All these new features are achieved by adding metadata to the audio, which is defined during production and offers content providers flexible control of interaction and rendering options. Thus, new possibilities are introduced, but also new requirements during the production process are imposed. This paper provides an overview of production scenarios using MPEG-H Audio along with examples of state-of-the-art NGA production workflows. Special attention is given to immersive music and broadcast applications as well as accessibility features.
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MPEG-H Audio is a Next Generation Audio (NGA) system offering a new audio experience for various applications: Object-based immersive sound delivers a new degree of realism and artistic freedom for immersive music applications, such as the 360 Reality Audio music service. Advanced interactivity options enable improved personalization and accessibility. Solutions exist, to create object-based features from legacy material, e.g., deep-learning-based dialogue enhancement. 'Universal delivery' allows for optimal rendering of a production over all kinds of devices and various ways of distribution like broadcast or streaming. All these new features are achieved by adding metadata to the audio, which is defined during production and offers content providers flexible control of interaction and rendering options. Thus, new possibilities are introduced, but also new requirements during the production process are imposed. This paper provides an overview of production scenarios using MPEG-H Audio along with examples of state-of-the-art NGA production workflows. Special attention is given to immersive music and broadcast applications as well as accessibility features.
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This article deals with the realization of an automated classification of loudspeaker enclosures. The acoustic load of the enclosure is reflected in the electrical impedance of the loudspeaker and is hence detectable from the point of view of the power amplifier. In order to classify the enclosures of passive one-way speakers, an artificial neural network is trained with synthetic impedance spectra based on equivalent electrical circuit models. The generalization capability is validated with measured test sets of closed, vented, band-pass and transmission-line enclosures. The resulting classification procedure works well within a synthetic test set. However, a good generalization to the measured test data requires further investigations to achieve better separation between the different vented enclosure types.
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This article deals with the realization of an automated classification of loudspeaker enclosures. The acoustic load of the enclosure is reflected in the electrical impedance of the loudspeaker and is hence detectable from the point of view of the power amplifier. In order to classify the enclosures of passive one-way speakers, an artificial neural network is trained with synthetic impedance spectra based on equivalent electrical circuit models. The generalization capability is validated with measured test sets of closed, vented, band-pass and transmission-line enclosures. The resulting classification procedure works well within a synthetic test set. However, a good generalization to the measured test data requires further investigations to achieve better separation between the different vented enclosure types.
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