Conventional channel-based room equalisation can reduce overall colouration caused by the room response, however it cannot separately correct the colouration caused by the late and early parts of the response, or consider the reverberance in the source signal. A room compensation method is developed here for a source signal in which the dry source sound and the associated target reverberant response are encoded separately, which is possible in an object-based audio framework. The target response is modified using the reproduction room response. Subject to some conditions the combined response approximates the target, with accurate early and late equalisations, reverberant balance, and decay timing. Stochastic assumptions are used to simplify the processing, enabling efficient real-time processing of the encoded audio.

Compensated amplitude panning (CAP) is a spatial audio reproduction method for loudspeakers that takes the listener head orientation into account. It can produce stable images in any direction using only two loudspeakers. In its original form, CAP is inherently an object-based method, with each image produced separately. An exact and efficient method is presented here for dynamically decoding a first order Ambisonic encoding, which is equivalent to using CAP to separately reproduce the constituents of the encoding. Both the stereo and multichannel cases are considered.

Conventional amplitude panning can be used to produce images of distant objects. An extended panning method is presented that can also produce image cues for the near-field region, by the control of Inter-aural Level Difference cues in the low frequency range below ~1000 Hz. The approach has grown from an adaptive panning method that corrects for the dependence of image direction on head orientation. Stereo panning functions are derived from a general formulation. A single first order filter is required for each image. The method is tested by simulating a range of configurations using measured Head Related Transfer Functions, and also with listening tests. The results confirm the ability of the method to control near-field cues, while also compensating image direction for head rotation.

Amplitude panning produces interaural time difference (ITD) cues that help localize images in directions between loudspeakers. However, if the panning gains are static, then the ITD cues produced in this way vary inconsistently as the listener's head rotates, compared with a real source, and so the dynamic ITD cues are inaccurate. This effect destabilizes the perception of the image and overall scene, and is worse for loudspeakers that are more widely spaced relative to the listener. Based on a simple head model that is accurate in the low-frequency ITD regime, the ITD is calculated for a general field, including those produced by panning. A simple formula is derived relating head orientation, image direction, and a field description vector. Panning functions are then found that compensate for head orientation and are valid for any image direction. For the special case when the listener is facing the image, the functions are equivalent to vector base amplitude panning. The performance is first assessed objectively using measured binaural responses, rather than the simple head model. Subjective comparison is then made with pre-existing listening tests and new listening tests in which the listener's head is tracked to control the panning gains in real-time. These show that images can be stabilized as predicted, and, furthermore, that with the same panning functions, images can be produced in all directions using two loudspeakers placed in front.

Object-based audio is an emerging representation for audio content, where content is represented in a reproduction-format-agnostic way and, thus, produced once for consumption on many different kinds of devices. This affords new opportunities for immersive, personalized, and interactive listening experiences. This paper introduces an end-to-end object-based spatial audio pipeline, from sound recording to listening. A high-level system architecture is proposed, which includes novel audio-visual interfaces to support object-based capture and listener-tracked rendering, and incorporates a proposed component for objectification, that is, recording content directly into an object-based form. Text-based and extensible metadata enable communication between the system components. An open architecture for object rendering is also proposed. The system's capabilities are evaluated in two parts. First, listener-tracked reproduction of metadata automatically estimated from two moving talkers is evaluated using an objective binaural localization model. Second, object-based scene capture with audio extracted using blind source separation (to remix between two talkers) and beamforming (to remix a recording of a jazz group) is evaluated with perceptually motivated objective and subjective experiments. These experiments demonstrate that the novel components of the system add capabilities beyond the state of the art. Finally, we discuss challenges and future perspectives for object-based audio workflows.

Sound fields can be encoded with a fixed number of signals, using microphones or panning functions. The sound field may later be reproduced approximately by decoding the signals to a loudspeaker array. The Stereo and Ambisonic systems provide examples. A framework is presented for addressing general questions about such encodings. The first problem considered is the conversion between encodings. The solution is applied to the decoding of scene encodings to a loudspeaker array. This is generalized to the decoding of subscenes where the resolution is focused in an angular window. Within an object-based audio framework such subscenes are useful for representing complex objects without using all the channels required for a full scene. The second problem considered is the compression of a scene encoding to a smaller encoding, from which the original can be reconstructed. The spatial distribution of compression error can be controlled.

In this paper, we propose a system for private sound which is based on the weighted pressure matching method (WPMM). The aim is to design the input signals to an array of loudspeakers that allow for the synthesis of a target field defined with large amplitude variations between the so-called dark points and the listener's position. The system enables listeners to control the trade-off between directivity performance and the accuracy of reproduction of the target field at the listening position when the input energy to the array is limited. This is achieved by calculating the WPMM weight in the dark zone based on a constraint on the characteristics of the sound field in the listening zone. The system is validated for a number of predefined use-case scenarios. The results of the experiments in an anechoic environment with a circular array prototype show that listeners can control the performance trade-off in a wide frequency range. In the second part of the paper, algorithms are presented for the fast update of the input signals when the user selects a new value of the performance constraint.