Scene-based spatial audio formats, such as Ambisonics, are playback system agnostic and may therefore be favoured for delivering immersive audio experiences to a wide range of (potentially unknown) devices. The number of channels required to deliver high spatial resolution Ambisonic audio, however, can be prohibitive for low-bandwidth applications. Therefore, this paper proposes a compression codec, which is based upon the parametric higher-order Directional Audio Coding (HO-DirAC) model. The encoder downmixes the higher-order Ambisonic (HOA) input audio into a reduced number of signals, which are accompanied by perceptually-motivated scene parameters. The downmixed audio is coded using a perceptual audio coder, whereas the parameters are grouped into perceptual bands, quantized, and downsampled. On the decoder side, low Ambisonic orders are fully recovered. Not fully recoverable HOA components are synthesized according to the parameters. The results of a listening test indicate that the proposed parametric spatial audio codec can improve the adopted perceptual audio coder, especially at low to medium-high bitrates, when applied to fifth-order HOA signals.

Delivering high-quality spatial audio in the Ambisonics format requires extensive data bandwidth, which may render it inaccessible for many low-bandwidth applications. Existing widely-available multi-channel audio compression codecs are not designed to consider the characteristic inter-channel relations inherent to the Ambisonics format, and thus may not leverage this knowledge to optimise the compression. Therefore, this article proposes a spatial audio compression algorithm, based on a novel reformulation of the Higher-Order Directional Audio Coding (HO-DirAC) method, which is specifically intended for compressing higher-order Ambisonic audio streams. The methodology builds upon the concept of a spherical filter bank acting in the spherical harmonic domain. This results in directionally constrained sound-field estimates and parameterization, which may be utilized to reconstruct the input Ambisonic signals with minimal perceived loss of quality. The results of a listening experiment indicate high perceptual quality when using six or more audio transport channels to deliver fifth-order (36 channels) Ambisonic sound scenes. The proposed formulation is also designed with low computational complexity in mind and may therefore be well suited for compressing Ambisonic sound scenes for a wide range of applications.

The decaying sound field in rooms is typically described by energy decay functions (EDFs). Late reverberation can deviate considerably from the ideal diffuse field, for example, in multiple connected rooms or non-uniform absorption material distributions. This paper proposes the common-slope model of late reverberation. The model describes spatial and directional late reverberation as linear combinations of exponential decays called common slopes. Its fundamental idea is that common slopes have decay times that are invariant across space and direction, while their amplitudes vary across both. We explore different approaches for determining the common slopes for large EDF sets describing different source-receiver configurations of the same environment. Among the presented approaches, the k-means clustering of decay times is the most general. Our evaluation shows that the common-slope model introduces only a small error between the modeled and the true EDF, while being considerably more compact than the traditional multi-exponential model. The amplitude variations of the common slopes yield interpretable room acoustic analyses. The common-slope model has potential applications in all fields relying on late reverberation models, such as source separation, dereverberation, echo cancellation, and parametric spatial audio rendering.

This article proposes a parametric signal-dependent method for the task of encoding microphone array signals into Ambisonic signals. The proposed method is presented and evaluated in the context of encoding a simulated seven-sensor microphone array, which is mounted on an augmented reality headset device. Given the inherent flexibility of the Ambisonics format, and its popularity within the context of such devices, this array configuration represents a potential future use case for Ambisonic recording. However, due to its irregular geometry and non-uniform sensor placement, conventional signal-independent Ambisonic encoding is particularly limited. The primary aims of the proposed method are to obtain Ambisonic signals over a wider frequency band-width, and at a higher spatial resolution, than would otherwise be possible through conventional signal-independent encoding. The proposed method is based on a multi-source sound-field model and employs spatial filtering to divide the captured sound-field into its individual source and directional ambient components, which are subsequently encoded into the Ambisonics format at an arbitrary order. It is demonstrated through both objective and perceptual evaluations that the proposed parametric method outperforms conventional signal-independent encoding in the majority of cases.

Decomposing a sound-field into its individual components and respective parameters can represent a convenient first-step towards offering the user an intuitive means of controlling spatial audio effects and sound-field modification tools. The majority of such tools available today, however, are instead limited to linear combinations of signals or employ a basic single-source parametric model. Therefore, the purpose of this paper is to present a parametric framework, which seeks to overcome these limitations by first dividing the sound-field into its multi-source and ambient components based on estimated spatial parameters. It is then demonstrated that by manipulating the spatial parameters prior to reproducing the scene, a number of sound-field modification and spatial audio effects may be realised; including: directional warping, listener translation, sound source tracking, spatial editing workflows and spatial side-chaining. Many of the effects described have also been implemented as real-time audio plug-ins, in order to demonstrate how a user may interact with such tools in practice.

The measurement of room acoustics plays a wide role in audio research, from physical acoustics modelling and virtual reality applications to speech enhancement. While vast literature exists on position-dependent room acoustics and coupling of rooms, little has explored the transition from one room to its neighbour. This paper presents the measurement and analysis of a dataset of spatial room impulse responses for the transition between four coupled room pairs. Each transition consists of 101 impulse responses recorded using a fourth-order spherical microphone array in 5 cm intervals, both with and without a continuous line-of-sight between the source and microphone. A numerical analysis of the room transitions is then presented, including direct-to-reverberant ratio and direction of arrival estimations, along with potential applications and uses of the dataset.

Recent work on acoustic parameter estimation indicates that geometric room volume can be useful for modeling the character of an acoustic environment. However, estimating volume from audio signals remains a challenging problem. Here we propose using a convolutional neural network model to estimate the room volume blindly from reverberant single-channel speech signals in the presence of noise. The model is shown to produce estimates within approximately a factor of two to the true value, for rooms ranging in size from small offices to large concert halls.

A powerful and flexible approach to record or encode a spatial sound scene is through spherical harmonics (SHs), or Ambisonics. An SH-encoded scene can be rendered binaurally by applying SH-encoded head-related transfer functions (HRTFs). Limitations of the recording equipment or computational constraints dictate the spatial reproduction accuracy, thus rendering might suffer from spatial degradation as well as coloration. This paper studies the effect of tapering the SH representation of a binaurally rendered sound field in conjunction with its spectral equalization. The proposed approach is shown to reduce coloration and thus improves perceived audio quality.

A method for computing and sharpening angular spectra, derived from low-order ambisonic signals, is presented in this paper, which is intended for high-resolution directional sound-field visualisation. The method relies on a re-assignment principle, whereby the directional energy for each grid point is assigned to a new direction, which corresponds to a direction-of-arrival (DoA) estimate within a spatially-localised region, centred around the respective grid point. This leads to the concentration of energy around the true sources, and hence, to sharper angular spectra than that of steered response power (SRP) beamformers of maximum directivity, with the same order of ambisonic input. It is demonstrated that the proposed method, when using low-order input, can achieve similar results to the SRP approach of much higher order.

We study the detailed temporal evolution of echo density in impulse responses for applications in acoustic analysis and rendering on general environments. For this purpose, we propose a smooth sorted density measure that yields an intuitive trend of echo density growth with time. This is fitted with a general power-law model motivated from theoretical considerations. We validate the framework against theory on simple room geometries and present experiments on measured and numerically simulated impulse responses in complex scenes. Our results show that the growth power of echo density is a promising statistical parameter that shows noticeable, consistent differences between indoor and outdoor responses, meriting further study.

Current methods for immersive playback of spatial sound content aim at flexibility in terms of encoding and decoding, abstracting the two from the recording or playback setup. Ambisonics constitutes such a method, that is however signal-independent, and at low spatial resolutions fails to provide appropriate spatialization cues to the listener, with potential severe colouration effects and localization ambiguity. We present a new signal-dependent method for parametric analysis and synthesis of ambisonic sound scenes that takes advantage of the flexibility of Ambisonics as a spatial audio format, while improving reproduction. The proposed approach considers a more general acoustic model than previous proposals, with multiple source signals and a non isotropic ambient component. According to a listening test using headphones, the method is perceived closer to binaural reference sound scenes than ambisonic playback.

The active intensity vector (AIV) is a common descriptor of the sound field. In microphone array processing, AIV is commonly approximated with beamforming operations and utilized as a direction of arrival (DOA) estimator. However, in its original form, it provides inaccurate estimates in sound field conditions where coherent sound sources are simultaneously active. In this work we utilize a higher order intensity-based DOA estimator on spatially-constrained regions (SCR) to overcome such limitations. We then apply 1-dimensional (1D) histogram processing on the noisy estimates for multiple DOA estimation. The performance of the estimator is shown with a 7-channel mobile microphone array, in reverberant conditions and under different signal-to-noise ratios.

Sound source localization in three dimensions with microphone arrays is an active field of research, applicable in sound enhancement, source separation, and sound field analysis. In this contribution we propose a method for three dimensional multiple sound source localization in reverberant environments. We employ a spatially constrained steered response beamformer on a spherical sector centered at the direction of arrival (DOA) estimates of the intensity vector. Experiments are performed in both simulated and real acoustical environments with a spherical microphone array for multiple sound sources under different reverberation and signal-to-noise ratio (SNR) conditions. The performance of the proposed method is compared with our previously proposed work and a subspace method in the spherical harmonic domain. The results demonstrate a significant improvement in terms of localization accuracy.

Spatial filtering with microphone arrays is a technique that can be utilized to obtain the signal of a target sound source from a specific direction. Typical approaches in the field of audio underperform in practical environments with multiple sound sources and diffuse sound. In this contribution, we propose a postfiltering technique to suppress the effect of interferers and diffuse sound. The proposed technique utilizes the cross-spectral estimates of the output of two beamformers to formulate a time-frequency soft masker. The beamformers' outputs are used only for parameter estimation and not for generating an audio signal. Two sets of beamformer weights, a constant and an adaptive, are applied to the microphone array signals for the parameter estimation. The weights of the constant beamformer are designed such that they provide a spatially narrow beam pattern that is time and frequency invariant, having a unity gain toward the direction of interest. The weights of the adaptive beamformer are formulated using linearly constrained optimization with the constraint of weighted orthogonality with respect to the constant beamformer weights, as well as the unity gain toward the look direction. The orthogonality constraint provides diffuse sound suppression while the unity gain distortionless response. The cross spectrum of these two beamformers provides the target energy at a given look direction for the post filter. The study focuses on compact microphone arrays with which the typical beamforming techniques feature a tradeoff between noise amplification and spatial selectivity, especially in the low frequency region. The proposed method is evaluated with instrumental measures and listening tests under different reverberation times, in dual and multitalker scenarios. The evaluation shows that the proposed method provides a better performance when compared with a previous state-of-the-art spatial filter based on cross-pattern coherence, a linearly constrained beamformer and a Wiener postfilter.

The spatial capture patterns according to head-related transfer-functions (HRTFs) can be approximated using linear beamforming techniques. However, assuming a fixed spatial aliasing frequency, with reduction of the number of sensors and thus the array size, the linear approach leads to an excessive amplification of the microphone noise, unless the beam patterns are made broader than determined by the HRTFs. An adaptive technique is proposed that builds upon the assumption that the binaural perception is largely determined by a set of short-time inter-aural parameters in frequency bands. The parameters are estimated from the noisy HRTF beam pattern signals as a function of time and frequency. As a result of temporal averaging, the effect of the noise is mitigated while the perceptual spatial information is preserved. Signals with higher SNR from broader patterns are adaptively processed to obtain the parameters from the estimation stage by means of least-squares optimized mixing and decorrelation. Listening tests confirmed the perceptual benefit of the proposed approach with respect to linear techniques.

A method for direction-of-arrival (DOA) and diffuseness estimation is presented, which proves to be effective above the spatial aliasing frequency of the microphone array in use. The method assumes symmetrical circular or spherical arrays of directional microphones or microphone mounted on a rigid baffle, and it exploits the inherent directionality of the array at high frequencies. The DOA and diffuseness estimators are shown to exhibit low estimation error above the spatial aliasing limit, compared to commonly used intensity-based estimators. A low-error broadband scheme that combines the intensity-based method and the new one is proposed for the ranges below and above aliasing respectively.

A parametric spatial filtering algorithm with a fixed beam direction is proposed in this paper. The algorithm utilizes the normalized cross-spectral density between signals from microphones of different orders as a criterion for focusing in specific directions. The correlation between microphone signals is estimated in the time-frequency domain. A post-filter is calculated from a multichannel input and is used to assign attenuation values to a coincidentally captured audio signal. The proposed algorithm is simple to implement and offers the capability of coping with interfering sources at different azimuthal locations with or without the presence of diffuse sound. It is implemented by using directional microphones placed in the same look direction and have the same magnitude and phase response. Experiments are conducted with simulated and real microphone arrays employing the proposed post-filter and compared to previous coherence-based approaches, such as the McCowan post-filter. A significant improvement is demonstrated in terms of objective quality measures. Formal listening tests conducted to assess the audibility of artifacts of the proposed algorithm in real acoustical scenarios show that no annoying artifacts existed with certain spectral floor values. Examples of the proposed algorithm can be found online at http://www.acoustics.hut.fi/projects/cropac/soundExamples.

Directional audio coding (DirAC) is a parametric time-frequency domain method for processing spatial audio based on psychophysical assumptions and on energetic analysis of the sound field. Methods to use DirAC in spatial sound synthesis for virtual worlds are presented in this article. Formal listening tests are used to show that DirAC can be used to position and to control the spatial extent of virtual sound sources with good audio quality. It is also shown that DirAC can be used to generate reverberation for N-channel horizontal listening with only two monophonic reverberators without a prominent loss in quality when compared with quality obtained with N-channel reverberators.

This paper proposes a method for analyzing the direction of the arrival of sound by estimating the sound intensity vector from the pressure and energy gradients of closely-spaced omnidirectional microphones depending on frequency. Microphones with relatively large housing, which cause shadowing, are used here to provide inter microphone level differences in order to compute the energy gradients at high frequencies. The proposed method is evaluated in the direction analysis of a spatial-sound processing technique, Directional Audio Coding (DirAC). It is shown that the method provides a reliable direction estimation at the entire audio frequency range, whereas the traditional method employing the pressure gradients produces correct estimation in a limited frequency window only.

A method to transform 5-channel surround sound signals to B-format is proposed, which provides unaltered spatial qualities when reproduced with directional audio coding (DirAC). The proposed method simulates anechoic B-format recording of the signals with two different virtual loudspeaker configurations, which are combined according to time-frequency analysis of diffuseness of the virtual sound field.

The localization of virtual sources generated with different two-dimensional (2-D) multichannel reproduction systems has been studied by means of auditory model simulations and listening tests. The reproduction was implemented with typical five- and eight-channel loudspeaker setups. The microphone systems used were first- and second-order Ambisonics as well as a spaced microphone technique. Pair-wise panning was also studied. The results show that the auditory model can be used in the prediction of perceived direction in multichannel sound reproduction near the median plane. Some systematic deviations between the model predictions and the listening test results were found farther from the median plane. The frequency-dependent capability to produce narrow-band virtual sources to targeted directions is reported for the studied systems.