Measured Room Impulse Responses Research Articles

Performance of low-frequency sound zones with very fast room impulse response measurements.

Sound zone methods aim to control the sound field produced by an array of loudspeakers to render a given audio content in specific areas while making it almost inaudible in others. At low frequencies, control filters are based on information of the electro-acoustical path between loudspeakers and listening areas, contained in the room impulse responses (RIRs). This information can be acquired wirelessly through ubiquitous networks of microphones. In that case and for real-time applications in general, short acquisition and processing times are critical. In addition, limiting the amount of data that should be retrieved and processed can also reduce computational demands. Furthermore, such a framework would enable fast adaptation of control filters in changing acoustic environments. This work explores reducing the amount of time and information required to compute control filters when rendering and updating low-frequency sound zones. Using real RIR measurements, it is demonstrated that in some standard acoustic rooms, acquisition times on the order of a few hundred milliseconds are sufficient for accurately rendering sound zones. Moreover, an additional amount of information can be removed from the acquired RIRs without degrading the performance.

Determination of the sound absorption coefficient of ETFE cushions in-situ using the genetic material optimizer in Odeon®

ETFE cushions are used as cladding in predominantly mid to large size architectural projects. Smaller cushions are about 10 m2 in size and the biggest single cushions can be several hundreds of square metres large. They are composed of ETFE membranes a few hundred of micrometres thick. From a point of view of room acoustics, their acoustic transparency, which increases with decreasing frequency, makes them to effectively act like sound absorbers. Their voluminous nature and transparency make it challenging to measure the sound absorption coefficient of ETFE cushions in a laboratory. Using the genetic material optimizer of Odeon® software, the effective sound absorption coefficient of ETFE cushions in four rooms was extracted from room acoustic parameters, which were in turn derived from measured room impulse response data. The results were compared and interpreted by the help of theoretical modelling and measurements on small cushions in a reverberant room. There is a relatively good agreement between the three types of results, possible causes for the differences are explained in the paper.

An augmented diffusion algorithm with bidirectional communication for a distributed active noise control system.

Recent studies on diffusion adaptation for distributed active noise control (DANC) systems have attracted significant research interest due to their balance between computational burden and stability compared to conventional centralized and decentralized adaptation schemes. The conventional multitask diffusion FxLMS algorithm assumes that the converged solutions of all control filters are consistent to each other, which is unrealistic in practice hence results in inferior performance in noise reduction. An augmented diffusion FxLMS algorithm has been proposed to overcome this problem, which adopts a neighborhood-wide adaptation and node-based combination approach to mitigate the bias in the converged solution of the multitask diffusion algorithms. However, the improvement comes at the expense of a higher computational burden and communication cost. All existing DANC systems, including the multitask and augmented diffusion algorithms, assume one-way communication between nodes. By contrast, this paper proposes a bidirectional communication scheme for the augmented diffusion algorithm to further reduce the memory requirement, computational burden, and communication cost. Simulation results in the free field and with measured room impulse responses both demonstrate that the proposed augmented diffusion algorithm with bidirectional communication can achieve a faster convergence speed than that based on one-way communication with a lower memory, computation, and communication burden.

Direct sound field estimation based on sound source modeling with sparse equivalent sources

The measurement of multi-point room impulse responses (RIRs) is challenging because it requires many microphones or a microphone traverse system. In our previous study, we proposed a spatial extrapolation method to measure early RIRs by the locally-positioned microphones. However, the estimation accuracy was degraded at a far distance from the microphones owing to the directivity of the sound source. In this study, we proposed a modeling method to estimate a direct sound field using a source radiation model based on the sparse equivalent source method. First, the source radiation was modeled using an enclosed microphone array. Then, we modeled the direct sound field using locally positioned microphones. The evaluation experiment was conducted in an anechoic chamber under 2.5D condition.

A binaural room impulse response dataset and Shorelining psychophysical task for the evaluation of auditory sensory augmentation

Sensory augmentation using spatial sound presented in augmented-reality (AR) can assist people with low vision or blindness in navigating their environment (Katz et al., 2012). Nonetheless, in many situations, the poor quality of the binaural sound rendered using current tool sets limits the potential capability of the assistive technology. In particular, acoustic environments with near-field sources and reflections pose significant challenges. In this work, we provide a reference binaural room impulse response (BRIR) dataset with near-field sources and reflections and an associated shorelining psychophysical task that is useful for the evaluation of AR spatial audio. The dataset consists of 12∼small loudspeakers arranged on a 3-by-4 grid in a complex acoustic environment. BRIR measurements are recorded using the Head and Torso Simulator (HATS) for 17∼different receiver positions with a 5o angular resolution. Room impulse response measurements are also recorded using the Eigenmike for each of the 17 receiver positions. Using the Razer Anzu smart glasses to render the binaural AR spatial audio, we compare psychophysical performance on the shorelining navigation task using the recorded dataset and various existing binaural AR tool sets.

Sound field reproduction based on Pressure Matching with transfer functions modeled by equivalent sources and image sources

Pressure matching (PM) method is an effective method to control a sound field using many loudspeakers. It is difficult to implement PM method because it requires multi-point room impulse response (RIR) measurements. Multi-point measurements are challenging because they require a large number of microphones and a narrow sampling interval when dealing with high frequencies. Therefore, to synthesize a sound field in a local region, we proposed a PM method using estimated RIRs from only a small number of measurements based on the sparse Equivalent Source Method (ESM). In the previous method, we modeled the transfer functions considering only the direct sound from the loudspeaker. However, when the sound field is synthesized in the actual environment, the reflected sounds must be considered. In this study, we propose a PM method using the estimated transfer functions by sparse ESM based on the image source method considering the direct sound and early reflected sounds. In the experiment, we evaluated the accuracies of synthesized sound field by the proposed method compared to the methods only considering the direct sound.

Spatial Interpolation of Early Room Impulse Responses Using Equivalent Source method based on Grouped Image Sources

The Room Impulse Response (RIR), which indicates the propagation characteristics of sound, is used in various acoustical applications. In particular, multi-point measurement of RIRs is important for applications that require spatial information, and measurement of these is difficult. Previously, spatial interpolation methods of RIRs based on physical models have been proposed. Especially, the sparse Equivalent Source Method (ESM) with Image Source Method (ISM) acheive the spatial interpolation of the early reflected sounds with higher accuracy at high frequency. However, this method has a problem that when the order of reflected sounds to be estimated increases, it becomes difficult to find the optimal solutions because the number of bases increases. In this study, to reduce the number of bases in each optimization problem, we proposed a sparse ESM with the image sources grouped by the arrival times of reflected sounds. The optimization problem for each group of image sources is individually solved. In the simulation experiment, it is revealed that the proposed method can estimate higher-order reflections with higher accuracy compared to the conventional method. In addition, we found that the estimated region with high accuracy became broader.

Differences between measured and simulated room impulse responses

Simulation models based on geometrical acoustics mostly do not immediately deliver a simulated room impulse response, but intermediate results such as an energy histogram or an energy decay curve. At this point, further models are required to generate a room impulse response of the simulated environment, which are essential for the process of auralization. While for various simulated scenarios, the application of a reflection model based on a basic theory is sufficient, detailed comparisons of simulated and measured room impulse responses reveal differences which are attributed to the lack of diffuse reflections in the applied reflection model. These deviations can also substantially affect derived room acoustic parameters. This work presents and explains the shortcomings and discusses potential improvements to be considered in the simulation process.

A stacked self-attention network for two-dimensional direction-of-arrival estimation in hands-free speech communication

When making voice interactions with hands-free speech communication devices, direction-of-arrival estimation is an essential step. To address the detrimental influence of unavoidable background noise and interference speech on direction-of-arrival estimation, this paper introduces a stacked self-attention network system, a supervised deep learning method that enables utterance level estimation without requirement for any pre-processing such as voice activity detection. Specifically, alternately stacked time- and frequency-dependent self-attention blocks are designed to process information in terms of time and frequency, respectively. The former blocks focus on the importance of each time frame of the received audio mixture and perform temporal selection to reduce the influence of non-speech and interference frames, while the latter blocks are utilized to derive inner-correlation among different frequencies. Additionally, the non-causal convolution and self-attention networks are replaced by causal ones, enabling real-time direction-of-arrival estimation with a latency of only 6.25 ms. Experiments with simulated and measured room impulse responses, as well as real recordings, verify the advantages of the proposed method over the state-of-the-art baselines.

Data-driven local average room transfer function estimation for multi-point equalization.

Multi-point room equalization (EQ) aims to achieve a desired sound quality within a wider listening area than single-point EQ. However, multi-point EQ necessitates the measurement of multiple room impulse responses at a listener position, which may be a laborious task for an end-user. This article presents a data-driven method that estimates a spatially averaged room transfer function (RTF) from a single-point RTF in the low-frequency region. A deep neural network (DNN) is trained using only simulated RTFs and tested with both simulated and measured RTFs. It is demonstrated that the DNN learns a spatial smoothing operation: notches across the spectrum are smoothed out while the peaks of the single-point RTF are preserved. An EQ framework based on a finite impulse response filter is used to evaluate the room EQ performance. The results show that while not fully reaching the level of multi-point EQ performance, the proposed data-driven local average RTF estimation method generally brings improvement over single-point EQ.

Measuring the Acoustical Properties of the BBC Maida Vale Recording Studios for Virtual Reality

In this paper we present a complete acoustic survey of the British Broadcasting Corporation Maida Vale recording studios. The paper outlines a fast room acoustic measurement framework for capture of spatial impulse response measurements for use in three or six degrees of freedom Virtual Reality rendering. Binaural recordings from a KEMAR dummy head as well as higher order Ambisonic spatial room impulse response measurements taken using a higher order Ambisonic microphone are presented. An acoustic comparison of the studios is discussed, highlighting remarkable similarities across three of the recording spaces despite significant differences in geometry. Finally, a database of the measurements, housing the raw impulse response captures as well as processed spatial room impulse responses is presented.

Time–frequency methods for characterization of room impulse responses and decay time measurement

In the low frequency range, the reverberation of a room should be characterized by the decay time, which can be determined experimentally by various methods. In order to make accurate and precise measurements, the differences between these methods and their advantages should be known and quantified. In this work, the performance of four linear and four adaptive time–frequency impulse response analysis methods was evaluated with the aim to find the most accurate method for characterizing the decays of the room modes. The methods were compared using generated Prony test signals with known modal properties and measured room impulse responses were also examined. The decay time using the selected time–frequency impulse response method was then estimated in three rooms and the measurement results were compared with interrupted sine tone methods. It has been shown that the choice of measurement setup and analysis parameters has an important influence on the estimation of the decay time and its modal frequency. The time–frequency impulse response method using the window width optimized Stockwell transform, the continuous wavelet transform, or the Morlet wave method were found to be the most robust methods, and their applicability is also enhanced by the fact that only a single measurement is required for the selected microphone position. The presented test methods could be used to evaluate the performance of other approaches for the evaluation of reverberation below the Schroeder frequency or the ability of measurement and signal processing techniques to characterize low frequency transient signals.

Spatial room impulse response measurement and post-processing for virtual reproduction of a stereo sound system

Spatial room impulse responses (SRIRs) characterize the spatial, temporal, and spectral properties of the sound field received at a particular location in a room for a given source-receiver configuration. SRIRs can be captured using spherical microphone arrays and are useful both for evaluating the acoustic performance of a space and in applications where it is desired to auralize the sound field being characterized with varying signals being played from the source. In this work, SRIRs were measured in a living room (mid-frequency RT approximately 0.4 s) using an mh acoustics Eigenmike em32 as the receiver and both a studio monitor loudspeaker and a subwoofer as the sources. Studio monitor placements replicated a left-right-center stereo monitoring configuration, with the subwoofer on the floor below the center loudspeaker, while attempting to avoid source and receiver placement on estimated modal planes in the room. Details of the post-processing used to finalize the SRIRs for use as a virtual stereo sound system will be presented, including cross-over filtering, tuning, and correction of the overall frequency response to a curve that is favorable for in-room loudspeaker listening. Measurement system details, SRIR data visualizations, and RT estimates will also be discussed.

Signal-aware direction-of-arrival estimation using attention mechanisms

The direction-of-arrival (DOA) of sound sources is an essential acoustic parameter used, e.g., for multi-channel speech enhancement or source tracking. Complex acoustic scenarios consisting of sources-of-interest, interfering sources, reverberation, and noise make the estimation of the DOAs corresponding to the sources-of-interest a challenging task. Recently proposed attention mechanisms allow DOA estimators to focus on the sources-of-interest and disregard interference and noise, i.e., they are signal-aware. The attention is typically obtained by a deep neural network (DNN) from a short-time Fourier transform (STFT) based representation of a single microphone signal. Subsequently, attention has been applied as binary or ratio weighting to STFT-based microphone signal representations to reduce the impact of frequency bins dominated by noise, interference, or reverberation. The impact of attention on DOA estimators and different training strategies for attention and DOA DNNs are not yet studied in depth. In this paper, we evaluate systems consisting of different DNNs and signal processing-based methods for DOA estimation when attention is applied. Additionally, we propose training strategies for attention-based DOA estimation optimized via a DOA objective, i.e., end-to-end. The evaluation of the proposed and the baseline systems is performed using data generated with simulated and measured room impulse responses of a uniform-linear microphone array under various acoustic conditions, like reverberation times, noise, and source array distances. The data contains a single source-of-interest, noise, and directional interference. The best-performing systems are also evaluated using measured data. Our experiments show that DNNs used for DOA estimation are biased to the spectral source characteristics and the spectral attention distribution used during training (e.g., spectrally flat/sparse). We also show that this bias in the DOA estimator can be avoided if signal-processing methods are used in combination with attention. Overall, DOA estimation using attention in combination with signal-processing methods exhibits a far lower computational complexity than a fully DNN-based system; however, it yields comparable results.

A Compact Noise Covariance Matrix Model for MVDR Beamforming

Acoustic beamforming is routinely used to improve the SNR of the received signal in applications such as hearing aids, robot audition, augmented reality, teleconferencing, source localisation and source tracking. The beamformer can be made adaptive by using an estimate of the time-varying noise covariance matrix in the spectral domain to determine an optimised beam pattern in each frequency bin that is specific to the acoustic environment and that can respond to temporal changes in it. However, robust estimation of the noise covariance matrix remains a challenging task especially in non-stationary acoustic environments. This paper presents a compact model of the signal covariance matrix that is defined by a small number of parameters whose values can be reliably estimated. The model leads to a robust estimate of the noise covariance matrix which can, in turn, be used to construct a beamformer. The performance of beamformers designed using this approach is evaluated for a spherical microphone array under a range of conditions using both simulated and measured room impulse responses. The proposed approach demonstrates consistent gains in intelligibility and perceptual quality metrics compared to the static and adaptive beamformers used as baselines.

A study of a renovated broadcast control room with a concave enclosure

Broadcast control rooms are monitoring stations which can have many operators. One such room with ellipsoidal plan shaping was recently renovated. The original room had sufficient absorptive wall treatment, such that any focusing effects were less obvious, and the occupants could perform their work in relative comfort. The renovated space included much more computer screen equipment—so much so that the original treatment was covered, and the concave surface shaping was duplicated in hard surfaces. The resulting space was distracting for the occupants, due to whispering gallery effects, and at times could become excessively loud. In this talk, we discuss our process for measuring anomalous effects in the space using room impulse response measurement techniques, as well as our computer modelling approach, which helps us identify the surfaces implicated in the measured anomalies. We will also discuss our proposed solutions, and the challenges associated with each.

Power Response and Modal Decay Estimation of Room Reflections from Spherical Microphone Array Measurements Using Eigenbeam Spatial Correlation Model

Modal decays and modal power distribution in acoustic environments are key factors in deciding the perceptual quality and performance accuracy of audio applications. This paper presents the application of the eigenbeam spatial correlation method in estimating the time-frequency-dependent directional reflection powers and modal decay times. The experimental results evaluate the application of the proposed technique for two rooms with distinct environments using their room impulse response (RIR) measurements recorded by a spherical microphone array. The paper discusses the classical concepts behind room mode distribution and the reasons behind their complex behavior in real environments. The time-frequency spectrum of room reflections, the dominant reflection locations, and the directional decay rates emulate a realistic response with respect to the theoretical expectations. The experimental observations prove that our model is a promising tool in characterizing early and late reflections, which will be beneficial in controlling the perceptual factors of room acoustics.

Dynamic Binaural Rendering: The Advantage of Virtual Artificial Heads over Conventional Ones for Localization with Speech Signals

As an alternative to conventional artificial heads, a virtual artificial head (VAH), i.e., a microphone array-based filter-and-sum beamformer, can be used to create binaural renderings of spatial sound fields. In contrast to conventional artificial heads, a VAH enables one to individualize the binaural renderings and to incorporate head tracking. This can be achieved by applying complex-valued spectral weights—calculated using individual head related transfer functions (HRTFs) for each listener and for different head orientations—to the microphone signals of the VAH. In this study, these spectral weights were applied to measured room impulse responses in an anechoic room to synthesize individual binaural room impulse responses (BRIRs). In the first part of the paper, the results of localizing virtual sources generated with individually synthesized BRIRs and measured BRIRs using a conventional artificial head, for different head orientations, were assessed in comparison with real sources. Convincing localization performances could be achieved for virtual sources generated with both individually synthesized and measured non-individual BRIRs with respect to azimuth and externalization. In the second part of the paper, the results of localizing virtual sources were compared in two listening tests, with and without head tracking. The positive effect of head tracking on the virtual source localization performance confirmed a major advantage of the VAH over conventional artificial heads.

Spatial extrapolation of early room impulse responses in local area using sparse equivalent sources and image source method

The room impulse response (RIR) is important in most acoustic applications, such as the design of concert halls and sound field control, because it characterizes the sound propagation. The measurement of RIRs at multiple points is challenging, as it requires a huge microphone array or repeating the experiment by microphone replacement. Several RIR interpolation and extrapolation methods of RIRs have been developed for obtaining RIRs from multiple measurement points efficiently. Extrapolation methods offer more efficient RIR measurement compared to interpolation. However, previous studies focused on extrapolation at frequencies below 1 kHz, and the extrapolation at higher frequencies was difficult. In this study, we propose an extrapolation method for RIRs of direct sound and early reflections in a local area using a small number of measurement points. The proposed method represents the RIRs around the microphones using superpositions of sparse equivalent sources located around the loudspeaker and image sources. We conducted a measurement experiment in an anechoic chamber to estimate RIRs around microphones using sound-reflecting boards. From the experimental results with 2.5 dimensional conditions, the proposed method achieved about above 10 dB of signal to noise ratio (SNR) near the microphone array from 0.5–8.5 kHz. For the extrapolation accuracy over the entire evaluation area (0.6 × 0.54 m2), the proposed method improved the SNR by about 5–6 dB compared to results using the plane wave decomposition.

A Superfast Toeplitz Matrix Inversion Method for Single- and Multi-Channel Inverse Filters and Its Application to Room Equalization

This paper derives a superfast Toeplitz matrix inversion method using FFT techniques. The approach casts the non-periodic Toeplitz matrix solution into a periodic framework and uses the Woodbury matrix inverse identity to express the non-periodic solution as a correction to the time-windowed periodic solution. It is shown that the solution can be implemented using FFT techniques that avoid the calculation of a large matrix inverse. The method is implemented for both single- and multi-channel cases and typical computation times and accuracy are reported for the equalization of simulated and measured room impulse responses.