Simulating room transfer functions between transducers mounted on audio devices using a modified image source method.

The image source method (ISM) is often used to simulate room acoustics due to its ease of use and computational efficiency. The standard ISM is limited to simulations of room impulse responses between point sources and omnidirectional receivers. In this work, the ISM is extended using spherical harmonic directivity coefficients to include acoustic diffraction effects. These effects occur in practice when transducers are mounted on audio devices of finite spatial extent, e.g., modern smart speakers with loudspeakers and microphones. The proposed method is verified using finite element simulations of various loudspeaker and microphone configurations in a shoebox-shaped room. It is shown that the accuracy of the proposed method is related to the sizes, shapes, number, and positions of the devices inside a room. A simplified version of the proposed method, which can significantly reduce computational effort, is also presented. The proposed method and its simplified version can simulate room transfer functions more accurately than currently available image source methods and can aid the development and evaluation of speech and acoustic signal processing algorithms, including speech enhancement, acoustic scene analysis, and acoustic parameter estimation.

Online reverberation time and clarity estimation in dynamic acoustic conditions.

Previously proposed methods for estimating acoustic parameters from reverberant, noisy speech signals exhibit insufficient performance under changing acoustic conditions. A data-centric approach is proposed to overcome the limiting assumption of fixed source-receiver transmission paths. The obtained solution significantly enlarges the scope of potential applications for such estimators. The joint estimation of reverberation time RT60 and clarity index C50 in multiple frequency bands is studied with a focus on dynamic acoustic environments. Three different convolutional recurrent neural network architectures are considered to solve the tasks of single-band, multi-band, and multi-task parameter estimation. A comprehensive performance evaluation is provided that highlights the benefits of the proposed approach.

Two congruent cues are better than one: Impact of ITD-ILD combinations on reaction time for sound lateralization.

This letter presents a reaction time analysis of a sound lateralization test. Sounds from various directions were synthesized using interaural time-level difference (ITD-ILD) combinations, and human subjects performed left/right detection. Stimuli from the sides yielded quicker reactions and better class accuracy than from the front. Congruent ITD-ILD cues significantly improved both metrics. For opposing ITD-ILD cues, subjects' choices were mostly driven by the ITD, and the responses were significantly slower. The findings, obtained with an easily accessible methodology, corroborate the integrated processing of the binaural cues and promote the use of multiple congruent binaural cues in headphone reproduction.

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.

Acoustic reciprocity in the spherical harmonic domain: A formulation for directional sources and receivers.

Acoustic reciprocity states that the transfer function between a source and a receiver remains unchanged if the two are interchanged. An extension of acoustic reciprocity to the spherical harmonic domain has been derived in the literature between a directional source and a directional receiver. The present letter derives a reciprocal relation between source and receiver directivity coefficients, which facilitates the derivation of a transfer function in the spherical harmonic domain using directivity coefficients obtained via reciprocity. Additionally, reciprocity between transfer functions is extended for more general source and receiver directivities, which include acoustic scattering effects.

Comparing Direct and Indirect Methods of Audio Quality Evaluation in Virtual Reality Scenes of Varying Complexity.

Many quality evaluation methods are used to assess uni-modal audio or video content without considering perceptual, cognitive, and interactive aspects present in virtual reality (VR) settings. Consequently, little is known regarding the repercussions of the employed evaluation method, content, and subject behavior on the quality ratings in VR. This mixed between- and within-subjects study uses four subjective audio quality evaluation methods (viz. multiple-stimulus with and without reference for direct scaling, and rank-order elimination and pairwise comparison for indirect scaling) to investigate the contributing factors present in multi-modal 6-DoF VR on quality ratings of real-time audio rendering. For each between-subjects employed method, two sets of conditions in five VR scenes were evaluated within-subjects. The conditions targeted relevant attributes for binaural audio reproduction using scenes with various amounts of user interactivity. Our results show all referenceless methods produce similar results using both condition sets. However, rank-order elimination proved to be the fastest method, required the least amount of repetitive motion, and yielded the highest discrimination between spatial conditions. Scene complexity was found to be a main effect within results, with behavioral and task load index results implying more complex scenes and interactive aspects of 6-DoF VR can impede quality judgments.

Wind speed and direction estimation based on the spatial coherence of closely spaced microphones.

Wind-induced noise recorded with a compact microphone array can be exploited to infer the mean velocity of the free-field airflow. In this work, a model-based method to estimate the wind flow speed and direction is proposed that uses spectro-spatial correlations of closely spaced microphone signals. As shown in a recent work by the present authors, the normalized cross-power spectral density of flow-induced noise measured with closely spaced microphones, also referred to as the spatial coherence, can be approximated by a semi-empirical model, named the Corcos model. Due to the dependency of the Corcos model on the airflow velocity, the measured spatial coherence provides information on the sought quantity. Speed and direction can be resolved by fitting the measured spatial coherence to the analytical Corcos model in the least squares sense. The accuracy of the proposed method is investigated across a range of wind speed between 0.5 and 12 ms-1 and all directions, using observation lengths from 5 s to 1 h. The audio samples under test were recorded indoors and outdoors and labeled by an ultrasonic anemometer. The evaluation results show that the accuracy can be increased by reducing the time resolution.

Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions.

Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the performance of such systems is a simulation approach to test their robustness in the presence of disruptions. This approach cannot only replace experiments in early phases of development but could also be used to study susceptibility, robustness, response, and recovery in case of disruptions. The paper presents a simulation framework for a TDOA-based indoor ultrasound localization system and ways to introduce different types of disruptions. This framework can be used to test the performance of TDOA-based localization algorithms in the presence of disruptions. Resilience quantification results are presented for representative disruptions. Based on these quantities, it is found that localization with arc-tangent cost function is approximately 30% more resilient than the linear cost function. The simulation approach is shown to apply to resilience engineering and can be used to increase the efficiency and quality of indoor localization methods.

Estimation of locally reacting surface impedance at modal frequencies using an eigenvalue approximation technique.

The accuracy of computational models for acoustics is often limited by a lack of reliable information concerning the frequency-dependent impedance of surface materials. This lack of information stems from the unavailability of reliable measurement methods for low frequencies. In this work, an approach is proposed, using eigenvalue analysis, for estimating the locally reacting, frequency-dependent impedance of a sound-absorbing sample. In particular, an eigenvalue approximation method is proposed and used in tandem with an optimization routine to obtain surface impedance estimates of an installed sample at modal frequencies. It is shown, using finite element simulations of an impedance tube and a small reverberation room, that the proposed method can provide reasonable estimates of the surface impedance of a sample placed on a boundary surface.

Generalized intensity vector and energy density in the spherical harmonic domain: Theory and applications.

The acoustic intensity vector and energy density are perceptually relevant physical measures of a sound field that can be used in the context of sound field reproduction or acoustic parameter estimation. In this work, weighted spatial averaging of the intensity vector and energy density is investigated, and the results are expressed in terms of the spherical harmonic coefficients of the sound field. Higher-order spherical harmonic coefficients are incorporated by considering radial averaging. This radial averaging is then generalized, yielding the proposed generalized intensity vector and energy density. Direction-of-arrival and diffuseness estimators are constructed based on the generalized intensity vector and energy density. In the evaluation, the proposed parameter estimators are compared to existing state-of-the-art estimators using simulated signals containing directional, diffuse, and sensor-noise components.

Generating coherence-constrained multisensor signals using balanced mixing and spectrally smooth filters.

The spatial properties of a noise field can be described by a spatial coherence function. Synthetic multichannel noise signals exhibiting a specific spatial coherence can be generated by properly mixing a set of uncorrelated, possibly non-stationary, signals. The mixing matrix can be obtained by decomposing the spatial coherence matrix. As proposed in a widely used method, the factorization can be performed by means of a Choleski or eigenvalue decomposition. In this work, the limitations of these two methods are discussed and addressed. In particular, specific properties of the mixing matrix are analyzed, namely, the spectral smoothness and the mix balance. The first quantifies the mixing matrix-filters variation across frequency and the second quantifies the number of input signals that contribute to each output signal. Three methods based on the unitary Procrustes solution are proposed to enhance the spectral smoothness, the mix balance, and both properties jointly. A performance evaluation confirms the improvements of the mixing matrix in terms of objective measures. Furthermore, the evaluation results show that the error between the target and the generated coherence is lowered by increasing the spectral smoothness of the mixing matrix.

No dynamic visual capture for self-translation minimum audible angle.

Auditory localization is affected by visual cues. The study at hand focuses on a scenario where dynamic sound localization cues are induced by lateral listener self-translation in relation to a stationary sound source with matching or mismatching dynamic visual cues. The audio-only self-translation minimum audible angle (ST-MAA) is previously shown to be 3.3° in the horizontal plane in front of the listener. The present study found that the addition of visual cues has no significant effect on the ST-MAA.

Self-translation induced minimum audible angle.

The minimum audible angle has been studied with a stationary listener and a stationary or a moving sound source. The study at hand focuses on a scenario where the angle is induced by listener self-translation in relation to a stationary sound source. First, the classic stationary listener minimum audible angle experiment is replicated using a headphone-based reproduction system. This experiment confirms that the reproduction system is able to produce a localization cue resolution comparable to loudspeaker reproduction. Next, the self-translation minimum audible angle is shown to be 3.3° in the horizontal plane in front of the listener.

The stability of multichannel sound systems with time-varying mixing matrices.

Various time-varying algorithms have been applied in multichannel sound systems to improve the system's stability and, among these, frequency shifting has been demonstrated to reach the maximum stability improvement achievable by time-variation in general. However, the modulation artifacts have been found to diminish the gain improvement unusable for a higher number of channels and high-quality applications such as music reproduction. This paper proposes alternatively time-varying mixing matrices, which is an efficient algorithm corresponding to symmetric up and down frequency shifting. It is shown with a statistical approach that time-varying mixing matrices can as well achieve maximum stability improvement for a higher number of channels. A listening test demonstrates the improved quality of time-varying mixing matrices over frequency shifting.

Time-varying feedback matrices in feedback delay networks and their application in artificial reverberation.

This paper introduces a time-variant reverberation algorithm as an extension of the feedback delay network (FDN). By modulating the feedback matrix nearly continuously over time, a complex pattern of concurrent amplitude modulations of the feedback paths evolves. Due to its complexity, the modulation produces less likely perceivable artifacts and the time-variation helps to increase the liveliness of the reverberation tail. A listening test, which has been conducted, confirms that the perceived quality of the reverberation tail can be enhanced by the feedback matrix modulation. In contrast to the prior art time-varying allpass FDNs, it is shown that unitary feedback matrix modulation is guaranteed to be stable. Analytical constraints on the pole locations of the FDN help to describe the modulation effect in depth. Further, techniques and conditions for continuous feedback matrix modulation are presented.

Mixing time prediction using spherical microphone arrays.

Human perception of room acoustics depends among others on the time of transition from early reflections to late reverberation in room impulse responses, which is known as mixing time. In this letter, a multi-channel mixing time prediction method is proposed, which in contrast to state-of-the-art channel-based predictors accounts for spatiotemporal properties of the sound field. The proposed diffuseness-based method is compared with existing model- and channel-based prediction methods through measurements and acoustic simulations, and is shown to correlate well with the perceptual mixing time. Furthermore, insights into relations between prediction methods and mixing time definitions based on reflection density are presented.

On the spatial coherence in mixed sound fields and its application to signal-to-diffuse ratio estimation.

Many applications in spatial sound recording and processing model the sound scene as a sum of directional and diffuse sound components. The power ratio between both components, i.e., the signal-to-diffuse ratio (SDR), represents an important measure for algorithms which aim at performing robustly in reverberant environments. This contribution discusses the SDR estimation from the spatial coherence between two arbitrary first-order directional microphones. First, the spatial coherence is expressed as function of the SDR. For most microphone setups, the spatial coherence is a complex function where both the absolute value and phase contain relevant information on the SDR. Secondly, the SDR estimator is derived from the spatial coherence function. The estimator is discussed for different practical microphone setups including coincident setups of arbitrary first-order directional microphones and spaced setups of identical first-order directional microphones. An unbiased SDR estimation requires noiseless coherence estimates as well as information on the direction-of-arrival of the directional sound, which usually has to be estimated. Nevertheless, measurement results verify that the proposed estimator is applicable in practice and provides accurate results.

Maximum likelihood estimation of direction of arrival using an acoustic vector-sensor.

A vector-sensor consisting of a monopole sensor collocated with orthogonally oriented dipole sensors is used for direction of arrival (DOA) estimation in the presence of an isotropic noise-field or internal device noise. A maximum likelihood (ML) DOA estimator is derived and subsequently shown to be a special case of DOA estimation by means of a search for the direction of maximum steered response power (SRP). The problem of SRP maximization with respect to a vector-sensor can be solved with a computationally inexpensive algorithm. The ML estimator achieves asymptotic efficiency and thus outperforms existing estimators with respect to the mean square angular error (MSAE) measure. The beampattern associated with the ML estimator is shown to be identical to that used by the minimum power distortionless response beamformer for the purpose of signal enhancement.

On the angular error of intensity vector based direction of arrival estimation in reverberant sound fields.

An acoustic vector sensor provides measurements of both the pressure and particle velocity of a sound field in which it is placed. These measurements are vectorial in nature and can be used for the purpose of source localization. A straightforward approach towards determining the direction of arrival (DOA) utilizes the acoustic intensity vector, which is the product of pressure and particle velocity. The accuracy of an intensity vector based DOA estimator in the presence of noise has been analyzed previously. In this paper, the effects of reverberation upon the accuracy of such a DOA estimator are examined. It is shown that particular realizations of reverberation differ from an ideal isotropically diffuse field, and induce an estimation bias which is dependent upon the room impulse responses (RIRs). The limited knowledge available pertaining the RIRs is expressed statistically by employing the diffuse qualities of reverberation to extend Polack's statistical RIR model. Expressions for evaluating the typical bias magnitude as well as its probability distribution are derived.

Generating nonstationary multisensor signals under a spatial coherence constraint.

Noise fields encountered in real-life scenarios can often be approximated as spherical or cylindrical noise fields. The characteristics of the noise field can be described by a spatial coherence function. For simulation purposes, researchers in the signal processing community often require sensor signals that exhibit a specific spatial coherence function. In addition, they often require a specific type of noise such as temporally correlated noise, babble speech that comprises a mixture of mutually independent speech fragments, or factory noise. Existing algorithms are unable to generate sensor signals such as babble speech and factory noise observed in an arbitrary noise field. In this paper an efficient algorithm is developed that generates multisensor signals under a predefined spatial coherence constraint. The benefit of the developed algorithm is twofold. Firstly, there are no restrictions on the spatial coherence function. Secondly, to generate M sensor signals the algorithm requires only M mutually independent noise signals. The performance evaluation shows that the developed algorithm is able to generate a more accurate spatial coherence between the generated sensor signals compared to the so-called image method that is frequently used in the signal processing community.