Dts, Inc.

Amazon Technologies, Inc.

Guangji Shi

Edward Stein

Martin Walsh

Michael M Goodwin

David Corsello

Jean-Marc Jot

Philip Ryan Hilmes

Trausti Thor Kristjansson

Jan Aage Abildgaard Pedersen

Changxue Ma

Themis George Katsianos

Antonius A Kalker

Daekyoung Noh

Vlad Ionut Ursachi

Petronel Bigioi

Embodiments of systems and methods are described for estimating a position of a loudspeaker and notifying a listener if an abnormal condition is detected, such as an incorrect loudspeaker orientation or an obstruction in a path between the loudspeaker and a microphone array. For example, a front component of a multi-channel surround sound system may include the microphone array and a position estimation engine. The position estimation engine may estimate the distance between the loudspeaker and the microphone array. In addition, the position estimation engine may estimate an angle of the loudspeaker using a first technique. The position estimation engine may also estimate an angle of the loudspeaker using a second technique. The two angles can be processed to determine whether the abnormal condition exists. If the abnormal condition exists, a listener can be notified and be provided with suggestions for resolving the issue in a graphical user interface.

System and method for loudspeaker position estimation

A system that performs wall detection, range estimation, and/or corner detection to determine a position of a device relative to acoustically reflective surfaces. The device generates output audio using a loudspeaker, generates microphone audio data using a microphone array, performs beamforming to generate directional audio data and then generates impulse response data for each of a plurality of directions. The device may detect a peak in the impulse response data and determine a distance and/or direction to a reflective surface based on the peak. Based on a number of reflected surfaces and/or direction(s) of the reflected surfaces detected by the device, the device may classify the different directions and estimate where it is in the room, such as whether the device is in a corner, along one wall, or in an open area. By knowing its position relative to the room surfaces, the device may improve sound equalization.

Method for autonomous loudspeaker room adaptation

A method and a system for calibrating a surround sound system are disclosed. The calibration system can provide a graphical user interface for display comprising a visual representation of the room hosting a multichannel surround sound system. The graphical user interface can permit user input of gestures to place or make changes to the placement of icons representing one or more loudspeakers and a listener. The calibration system can estimate the positions of the one or more loudspeakers or the listener based on the placement of the icons in the model room. A spatial calibration based on the estimated positions can then be performed such that the multichannel surround sound system can render sound scenes more accurately.

Graphical user interface for calibrating a surround sound system

The method and apparatus described herein make use of multiple sets of head related transfer functions (HRTFs) that have been synthesized or measured at various distances from a reference head, spanning from the near-field to the boundary of the far-field. Additional synthetic or measured transfer functions maybe used to extend to the interior of the head, i.e., for distances closer than near-field. In addition, the relative distance-related gains of each set of HRTFs are normalized to the far-field HRTF gains.

Near-field binaural rendering

A system that performs wall detection, range estimation, and/or corner detection to determine a position of a device relative to acoustically reflective surfaces. The device generates output audio using loudspeaker(s), generates microphone audio data using a microphone array, and generates impulse response data for each of the microphones. The device may generate the impulse response data using an acoustic echo cancellation (AEC) component or multi-channel AEC (MC-AEC). The device may detect a peak in the impulse response data and determine a distance to a reflective surface based on the peak. Based on a number of reflected surfaces detected by the device, the device may classify a position of the device within the room, such as whether the device is in a corner, along one wall, or in an open area. By knowing the position relative to the room surfaces, the device may improve sound equalization and other processing.

Method for efficient autonomous loudspeaker room adaptation

Systems and methods discussed herein can provide three-dimensional audio virtualization with sweet spot adaptation. In an example, an audio processor circuit can be used to update audio signals for sweet spot adaptation based on information from at least one depth sensor or camera about a listener position in a listening environment.

Sweet spot adaptation for virtualized audio

The methods and apparatus described herein optimally represent full 3D audio mixes (e.g., azimuth, elevation, and depth) as 'sound scenes' in which the decoding process facilitates head tracking. Sound scene rendering can be modified for the listener's orientation (e.g., yaw, pitch, roll) and 3D position (e.g., x, y, z). This provides the ability to treat sound scene source positions as 3D positions instead of being restricted to positions relative to the listener. Sound scene rendering can be augmented by encoding depth to a source directly. This provides the ability to modify the transmission format and panning equations to support adding depth indicators during content production. Unlike typical methods that apply depth cues such as loudness and reverberation changes in the mix, this method would enable recovering the distance of a source in the mix so that it can be rendered for the final playback capabilities rather than those on the production side.

Ambisonic audio rendering with depth decoding

A GPEQ filter and tuning methods for asymmetric transaural audio reproduction on mobile consumer devices. The GPEQ filter includes an asymmetric FIR filter bank configured to normalize the magnitude responses of at least two audio speakers to a target response above a low frequency cross-over of the audio speakers as reproduced at the listener position and a symmetric IIR filter bank component configured to high pass filter above the low frequency cross-over and equalize the magnitude responses of the at least two audio speakers. In some embodiments the FIR filter bank is configured to normalize the group delay of the audio channels and in some embodiments the IIR filter bank includes an asymmetric IIR filter bank component configured to correct any residual asymmetry in the magnitude responses of the at least two audio speakers. Phase preservation may be accomplished using phase-balanced or phase-compensated IIR filter sections.

Gain phase equalization (GPEQ) filter and tuning methods for asymmetric transaural audio reproduction

The methods and apparatus described herein optimally represent full 3D audio mixes (e.g., azimuth, elevation, and depth) as 'sound scenes' in which the decoding process facilitates head tracking. Sound scene rendering can be performed for the listener's orientation (e.g., yaw, pitch, roll) and 3D position (e.g., x, y, z), and can be modified for a change in the listener's orientation or 3D position. As described below, the ability to render an audio object in both the near-field and far-field enables the ability to fully render depth of not just objects, but any spatial audio mix decoded with active steering/panning, such as Ambisonics, matrix encoding, etc., thereby enabling full translational head tracking (e.g., user movement) beyond simple rotation in the horizontal plane, or 6-degrees-of-freedom (6-DOF) tracking and rendering.

Audio rendering using 6-DOF tracking

A method for calibrating a surround sound system is disclosed. The method utilizes a microphone array integrated in a front center loudspeaker of the surround sound system or a soundbar facing a listener. Positions of each loudspeaker relative to the microphone array can be estimated by playing a test signal at each loudspeaker and measuring the test signal received at the microphone array. The listener's position can also be estimated by receiving the listener's voice or other sound cues made by the listener using the microphone array. Once the positions of the loudspeakers and the listener's position are estimated, spatial calibrations can be performed for each loudspeaker in the surround sound system so that listening experience is optimized.

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San Jose, CA, United States of America

Guangji Shi