Reverberation Characteristics Research Articles

Reverberation divergence in VR applications

This project aimed to investigate the correlation between virtual reality (VR) imagery and ambisonic sound. With the increasing popularity of VR applications, understanding how sound is perceived in virtual environments is crucial for enhancing the immersiveness of the experience. In the experiment, participants were immersed in a virtual environment that replicated a concert hall. Their task was to assess the correspondence between sound scenes (which differed in reverberation times and their characteristics) and the observed invariant visual scene. The research was conducted using paired tests. Participants were asked to identify the sound scene they considered more closely matched the concert hall seen in the VR goggles for each pair. Each sound scene differed in the employed impulse response. All the impulse responses were recorded in real venues such as concert halls, auditoriums, churches, etc. To provide a realistic auditory experience, the sound scenes were processed using third-order ambisonics and decoded using binaural techniques with HRTFs. The virtual concert hall was generated using the Unreal Engine and was the same for all the tests. One of the major conclusions drawn from the conducted research was confirming the role of spatial sound in creating immersive VR experiences. The study demonstrated that appropriately matching spatial sound to the VR visual scene is essential for achieving complete immersion. Additionally, expectations and preferences regarding reverberation characteristics in different types of spaces were discovered. These findings have significant implications for the design of virtual environments, and understanding these aspects can contribute to improving VR technology and creating more immersive and realistic virtual experiences for users.

Measurement method of the transient radiated noise in the reverberant pool

Transient radiated noise is the primary source of exposure for underwater targets due to its short duration and distinct spectral line characteristics. In order to accurately measure the sound source level of transient radiated noise, a reverberation method of radiated noise measurement based on power averaging processing in the frequency band is proposed. The power of the transient signal is obtained by using time-domain signal autocorrelation technology. The sound source level of the transient radiated noise in the frequency range of 500 kHz to 10 kHz is determined by the reverberant characteristics of the pool. The sound source level of the transient radiated noise in the frequency range of 1 kHz - 10 kHz is compared and measured in the anechoic tank. The deviation of the measurement results is less than 1.5 dB, which confirms the accuracy of the reverberant measurement method.

Towards liveness: collective memory and reproductions of studio reverberation

ABSTRACT Through a consideration of their reverberant characteristics, this article places representations of recording studios as an active cultural process that plays out through the recorded sounds such spaces become associated with. Like other heritage sites, the work to define, maintain, and allocate certain structures as unique or significant relies on the cultural process of collective memory. By focusing on the concept of sonic recollection, the reconfiguration of unique tracking room environments for “in the box” digital audio workstation software, exemplified through reverberation, is shown to draw from a network of people, sounds, and technologies that cumulatively reflect various stages of a recording studio’s trajectory. By uncovering this network – encompassing well-known and unnamed engineers, famous to merely aspiring recording artists, established or defunct studios and software companies, and technologies such as convolution reverb, all of which articulate one another in digital audio workstation software – it suggests that the theoretical underpinnings of collective memory studies are a useful tool of analysis to more fully frame reconstructions or representations of physical spaces undertaken through recorded sound, and that reverberation is an ideal metaphor for the work of collective memory.

Listening to the room: Disrupting activity of dorsolateral prefrontal cortex impairs learning of room acoustics

Navigating complex sensory environments is critical to survival, and brain mechanisms have evolved to cope with the wide range of surroundings. In noisy spaces listeners place more emphasis on early-arriving sound energy, nevertheless, reverberant energy is highly informative about those spaces per se, and human listeners show improved speech understanding when re-encountering known reverberant environments. We assessed the ability of listeners to perceive speech (Coordinate Response Measure corpus) in noisy and reverberant rooms. We mimicked the acoustic characteristics of real rooms using loudspeakers positioned within an anechoic chamber. Listeners were also exposed to repetitive transcranial stimulation (rTMS) to disrupt the dorsolateral prefrontal cortex activity (DLFPC), a region believed to play a role in statistical learning. Our data suggest listeners rapidly adapt to statistical characteristics of an acoustic environment to improve speech understanding. This ability is impaired when rTMS is applied bilaterally to the DLPFC. The data demonstrate that speech understanding in noise is best when exposed to a room with reverberant characteristics common to human-built environments. Our findings provide evidence for a reverberation “sweet spot” and the presence of brain mechanisms that might have evolved to cope with the acoustic characteristics of listening environments encountered every day.

A Shallow Seafloor Reverberation Simulation Method Based on Generative Adversarial Networks

Reverberation characteristics must be considered in the design of sonar. The research on reverberation characteristics is based on a large number of actual reverberation data. Due to the cost of trials, it is not easy to obtain actual lake and sea trial reverberation data, which leads to a lack of actual reverberation data. Traditionally, reverberation data are obtained by modeling the generation mechanism of seafloor reverberation. The usability of the models requires a large amount of actual seafloor reverberation data to verify. In terms of the reverberation modeling theory, scattering models are mostly empirical, computationally intensive and inefficient. In order to solve the above obstacles, we propose a shallow seafloor reverberation data simulation method based on the generative adversarial network (GAN), which uses a small amount of actual reverberation data as reference samples to train the GAN to generate more reverberation data. The reverberation data generated by the GAN are compared with that simulated by traditional methods, and it is found that the reverberation data generated by the GAN meet the reverberation characteristics. Once the network is trained, the reverberation data are generated with very little computation. In addition, the method is universal and can be applied to any sea area. Compared with the traditional method, this method has a simple modeling idea, less computation and strong universality. It can be used as an alternative method for sea trials to provide data support for the study of seafloor reverberation characteristics, and it has broad application prospects in antireverberation technology research and active sonar design.

Acoustic Feature Extraction Method of Rotating Machinery Based on the WPE-LCMV

Fault diagnosis plays an important role in the safe and stable operation of rotating machinery, which is conducive to industrial development and economic improvement. However, effective feature extraction of rotating machinery fault diagnosis is difficult in the complex sound field with characteristics of reverberation and multi-dimensional signals. Therefore, this paper proposes a novel acoustic feature extraction method of the rotating machinery based on the Weighted Prediction Error (WPE) integrating the Linear Constrained Minimum Variance (LCMV). The de-reverberation signal is obtained by inputting multi-channel signals into the WPE algorithm using an adaptive optimal parameters selection function with the sound field changes. Then, the incident angle going from the fault source to the center of the microphone array is calculated from the full-band sound field distribution, and the signal is de-noised and fused using the LCMV. Finally, the fault feature frequency is extracted from the fused signal envelope spectrum. The results of fault data analysis of the centrifugal pump test bench show that the Envelope Harmonic Noise Ratio (EHNR) is more than twice that of the original signal after the WPE-LCMV processing. Compared to the Recursive Least Squares and the Resonance Sparse Signal Decomposition (RLS-RSSD) and the parameter optimized Variational Mode Decomposition (VMD), the EHNR has a higher value for all types of faults after applying the WPE-LCMV processing. Furthermore, the proposed method can effectively extract the frequency of bearing faults.

Considerations about L2- and L1-norm regularizations for ultrasound reverberation characteristics imaging and vectoral Doppler measurement.

The L1-norm regularization is applied to ultrasonic reverberation characteristics imaging and vectoral Doppler measurement, of which performances are compared with those of L2-norm regularizations. The L1 regularization yields the sharper image than the L2 regularization. Alternatively, for the Doppler measurement, the L1 regularization yields less accuracy than the L2 regularization. Clinical Relevance- This study will permit us to perform quantitative ultrasonic reverberation characteristics and accurate vectoral Doppler observation.

Ocean acoustic boundary characterization multi-national experiments

The condition of the sea surface and seabed boundaries of the ocean often significantly affect the characteristics of acoustic signal propagation, reverberation and noise particularly in shallow water. A series of collaborative experiments were conducted from 2000 to 2009 to better understand the impact of ocean boundary characteristics on ocean acoustic signals in the frequency range of 100 – 5000 Hz. Acoustic measurements included long-range (waveguide) propagation, reverberation, and clutter as well as measurements of local boundary reflection and scattering. These were supported by oceanographic, geophysical and geologic measurements. Experimental locations included the Tyrrhenian Sea, Straits of Sicily, the New Jersey shelf, and the Scotian shelf with collaborators from NATO-STO CMRE and national laboratories and institutions from Italy, Canada, France, and the US. This talk will provide an overview of some of the main results from these experiments. [Research sponsored by CMRE(NATO), ONR(US), NUWC(US), INGV(IT), SHOM(FR), DRDC(CA), Italian Navy(IT).]

Interpolating the Directional Room Impulse Response for Dynamic Spatial Audio Reproduction

Virtual reality (VR) is increasingly important for exploring the real world, which has partially moved to virtual workplaces. In order to create immersive presence in a simulated scene for humans, VR needs to reproduce spatial audio that describes three-dimensional acoustic characteristics in the counterpart physical environment. When the user moves, this reproduction should be dynamically updated, which provides practical challenges because the bandwidth for continuously transmitting audio and video scene data may be limited. This paper proposes an interpolation approach for dynamic spatial audio reproduction using acoustic characteristics of direction and reverberation at limited numbers of positions, which are represented using a first order Ambisonics encoding of the room impulse response (RIR), called the directional RIR (DRIR). We decompose two known DRIRs into reflection components, before interpolating early dominant components for DRIR synthesis and utilizing DRIR recordings for accuracy evaluation. Results indicate that the most accurate interpolation is obtained by the proposed method over two comparative approaches, particularly in a simulated small room where most direction of arrival estimation errors of early components are below five degrees. These findings suggest precise interpolated DRIRs with limited data using the proposed approach, which is vital for dynamic spatial audio reproduction for VR applications.

Perceptual analysis of directional late reverberation

The late reverberation characteristics of a sound field are often assumed to be perceptually isotropic, meaning that the decay of energy is perceived as equivalent in every direction. In this paper, we employ Ambisonics reproduction methods to reassess how a decaying sound field is analyzed and characterized and our capacity to hear directional characteristics within late reverberation. We propose the use of objective measures to assess the anisotropy characteristics of a decaying sound field. The energy-decay deviation is defined as the difference of the direction-dependent decay from the average decay. A perceptual study demonstrates a positive link between the range of these energy deviations and their audibility. These results suggest that accurate sound reproduction should account for directional properties throughout the decay.

Testing Speech Perception with Cochlear Implants Through Digital Audio Streaming in a Virtual Sound Booth: A Feasibility Study

For patients who have received cochlear implants (CIs), speech-perception testing requires specialized equipment. This limits locations where these services can be provided, which can introduce barriers for provision of care. Providing speech test stimuli directly to the CI via wireless digital audio streaming (DAS) or wired direct audio input (DAI) allows for testing without the need for a sound booth (SB). A few studies have investigated the use of DAI for testing speech perception in CIs, but none have evaluated DAS. The goal of this study was to compare speech perception testing in CI users via DAS versus a traditional SB to determine if differences exist between the two presentation modes. We also sought to determine whether pre-processing the DAS signal with room acoustics (reverberation and noise floor) to emulate the SB environment would affect performance differences between the SB and DAS. In Experiment 1, speech perception was measured for monosyllabic words in quiet and sentences in quiet and in noise. Scores were obtained in a SB and compared to those obtained via DAS with unprocessed speech (DAS-U) for 11 adult CI users (12 ears). In Experiment 2, speech perception was measured for sentences in noise, where both the speech and noise stimuli were pre-processed to emulate the SB environment. Scores were obtained for 11 adult CI users (12 ears) in the SB, via DAS-U, and via DAS with the processed speech (DAS-P). For Experiment 1, there was no significant difference between SB and DAS-U conditions for words or sentences in quiet. However, DAS-U scores were significantly better than SB scores for sentences in noise. For Experiment 2, there was no significant difference between the SB and DAS-P conditions. Similar to Experiment 1, DAS-U scores were significantly better than SB or DAS-P scores. By pre-processing the test materials to emulate the noise and reverberation characteristics of a traditional SB, we can account for differences in speech-perception scores between those obtained via DAS and in a SB.

Relation between Direction-of-Arrival distribution of reflected sounds in late reverberation and room characteristics: Geometrical acoustics investigation

It has been reported that Direction-of-Arrival (DoA) distribution of reflected sounds is not isotropic in late reverberation. However, it is not clear how room characteristics contribute to the anisotropic DoA distribution. In this paper, the relation between DoA distribution in late reverberation and room characteristics is analyzed by using geometrical acoustic simulation and plane wave decomposition. The computational results showed that the DoA distribution in late reverberation is biased depending on the arrangement of absorptive surfaces and the shape of the room while the source position does not have prominent effects.

New efficient subband structures for blind source separation

Convolutive mixtures of signals generated by more than one source and acquired by a set of microphones are commonly found in acoustic signal processing applications. Subband methods have been proposed to reduce computational complexity and improve the convergence rate of adaptive algorithms developed for blind source separation of these mixtures, without significantly impairing steady-state performance. Oversampled discrete Fourier transform (DFT) filter bank is a usual option for the generation of subband signals in order to avoid harmful aliasing effects, thereby maintaining sufficient samples to estimate the subband signal statistics. In this paper, two new subband structures, composed of cosine-modulated filter banks (CMFB) with critical or oversampled sampling and low-order adaptive subfilters, are proposed for efficient blind source separation approach in convolutive mixtures of speech signals. A time-varying step-size procedure that provides better convergence rate for several reverberation characteristics is advanced. In addition, both computational complexity and steady-state performance of the proposed structures are compared to those of the standard fullband algorithm, to other subband structures with oversampling and critical sampling, and to frequency domain algorithm. The advanced solutions are capable of improving the source interference ratio (SIR) by more than 5 dB. Finally, two strategies are presented to minimize the effects of remaining aliasing in the proposed subband approaches, which obtain an additional gain of about 3 dB in the asymptotic SIR.

A Space-Time Adaptive Processing Method Based on Sparse Reconstruction of Reverberation Interference

Aiming at the problem of how to obtain reverberation samples and estimate their covariance matrix in the space-time adaptive processing(STAP) of sonar system, a new space-time adaptive processing method is proposed based on sparse reconstruction of reverberation in this paper. Firstly, according to the space-time distribution characteristics of reverberation received by moving platform sonar, a space-time steering dictionary for sparse reconstruction of reverberation is designed along the relation curve between Doppler frequency shift and incident cone angle cosine of the reverberation unit. Then, a reverberation sample in the rangecell under test (RUT) is reconstructed with high precision by sparse decomposition of signals obtained from the sonar array in the space-time steering dictionary. Finally, based on the prior information of reverberation probability distribution model, a sufficient number of reverberation samples are generated to meet the requirement of performance loss index on reverberation sample size in the space-time adaptive processing, so as to correctly obtain estimation of the covariance matrix of reverberation. This method can reconstruct the reverberation samples and estimate the reverberation covariance matrix directly from the data in RUT without relying on the auxiliary data from units adjacent to the RUT. Therefore, it is not only suitable for the environment with constant reverberation statistical characteristics, but also suitable for the environment with varying statistical characteristics. Simulation results of sonar forward-looking array and side-looking array indicate that the improvement factor of the proposed method is about 10dB lower than the traditional space-time adaptive processing method. So this new STAP method has good anti-reverberation performance.

Measurement-Based Feasibility Exploration on Detecting and Localizing Multiple Humans Using MIMO Radio Channel Properties

This paper explores the feasibility of using the multiple-input multiple-output (MIMO) radio channel properties to passively detect and localize multiple humans in indoor environments. We propose to utilize the unique reverberation characteristics of indoor channels for the purpose of detecting, and the power angular delay profile (PADP) for localizing humans. On the one hand, the reverberation time corresponds with the decay rate of multipath in a closed or partially closed cavity, and varies with the change of the number of humans or the moving of humans relative to the antennas at link ends. On the other hand, the PADP is proposed to be calculated by the Multiple Signal Classification (MUSIC) super resolution algorithm with frequency smoothing preprocessing. The proposed approach is evaluated based on real-world MIMO radio channel measurements obtained from a meeting room. Measurements with and without the presence of humans have been conducted, where the maximum number of humans considered is four. Humans facing different directions, either in parallel or orthogonal to the direct line between the transmit and the receive antennas have been taken into account. In term of the detection feasibility, it is found that the change of the number of humans as well as the change of their facing/moving directions inside the partial reverberant region can be reflected on the change of the reverberation time estimated from the power delay profile of channel. In term of the localization feasibility, it is found that single human location can be well associated to the peak of the variation of the PADP during his/her movement, while multiple humans' movements result in obvious power variation in the very vicinity of some of them, and also in the vicinity of some background objects that is far from target humans.

A method to virtually extend reverberation time of measured impulse responses without losing room coloration

For various audio and acoustical applications, it is useful to modify the reverberation time of a measured room impulse response. For example, it can be interesting for creating various modified impulse responses for convolution reverbs in video games or sound designs. With this in mind, it is proposed to modify an impulse response reverberation time while keeping the other reverberation characteristics, such as the frequency response, unaffected. Knowing how a typical impulse response is related to the room characteristics, we propose a new method. First, the impulse response of a room is measured. Then, the reverberation time is evaluated. This reverberation time is next approximated by Sabine-Eyring equation, resulting in an absorption coefficient. A new absorption coefficient is then manually provided to reach a new target reverberation time. Finally, the late reverberation of the original impulse response is convolved with a gaussian white noise to the desired length and stitched with appropriate decaying envelopes to the end of the initially measured impulse response. This paper illustrates that the method works based on simulations and that the modified impulse response is realistic and can be related to the actual room.For various audio and acoustical applications, it is useful to modify the reverberation time of a measured room impulse response. For example, it can be interesting for creating various modified impulse responses for convolution reverbs in video games or sound designs. With this in mind, it is proposed to modify an impulse response reverberation time while keeping the other reverberation characteristics, such as the frequency response, unaffected. Knowing how a typical impulse response is related to the room characteristics, we propose a new method. First, the impulse response of a room is measured. Then, the reverberation time is evaluated. This reverberation time is next approximated by Sabine-Eyring equation, resulting in an absorption coefficient. A new absorption coefficient is then manually provided to reach a new target reverberation time. Finally, the late reverberation of the original impulse response is convolved with a gaussian white noise to the desired length and stitched with appropriate dec...

Frequency-Dependence Characterization of Electromagnetic Reverberation in Indoor Scenarios Based on 1–40 GHz Channel Measurements

A novel model for the reverberation time is proposed in this letter, based on room electromagnetics theory. While the commonly used models consider absorption based on a constant rate of wall interactions within a given time, the proposed model takes the variance of interactions into account. Moreover, the frequency dependence of electromagnetic reverberation characteristics in indoor environments is experimentally investigated from 1 to 40 GHz. The reverberation time is found to be a decreasing function of frequency. A model is then developed to predict the room's quality factor, reverberation time, and average absorption coefficient. Good agreement is obtained with the limited results reported in the literature for similar scenarios. This approach aims to be an accurate alternative to the reverberation time measurements and computations in indoor environments by linking it to the theory of electromagnetic fields in cavities.

Estimation of Late Reverberation Characteristics from a Single Two-Dimensional Environmental Image Using Convolutional Neural Networks

Estimation of Late Reverberation Characteristics from a Single Two-Dimensional Environmental Image Using Convolutional Neural Networks

Analysis of seafloor reverberation related characteristics based on sea trial data

Ocean reverberation is one of the main factors affecting sonar performance. Studying the spatio-temporal correlation statistical characteristics of reverberation is of great significance for sonar detection and suppress reverberation, and is a problem that sonar designers have always been concerned about. This paper first gives an overview of the sea trial test; and analyzes the signal strength of the reverberation signals with different frequencies under different terrain conditions, which proves the reliability of the sea trial data. By processing the time-space correlation characteristics of the seabed reverberation data, the relationship between time-space correlation characteristics of the seabed reverberation data and the frequency and form of the transmitted signal and the seabed topography is obtained, which provides a theoretical reference for reverberation suppression and application.

Discrimination Between Broadband Underwater Target Echo and Reverberation Based on Signal Spectral Flatness Feature

Reverberation is the major interference of active detection, discrimination between target echo and reverberation is difficult when the reverberation is very strong. For the distinguishing of underwater target echo with strong interference, the modulation feature of echo and reverberation spectrum are characterized by signal spectral flatness measure, and the relationship between signal spectral flatness and target physical properties are theoretically formed. A method of discrimination between broadband underwater target echo and reverberation that based on signal spectral flatness characteristics difference is proposed and studied. Sea experiment results of complex underwater target broadband acoustic scattering have shown that signal spectral flatness characteristics of underwater target broadband echo and reverberation have obvious differences. Target echo and reverberation can be well distinguished using the proposed method.