# US 12,183,352 B2 · Multi-order optimized Ambisonics decoding > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,183,352 B2 - Document ID: US12183352B2 - Status: Granted - Kind: B2 - Application number: 17/932,650 - Filed: 2022-09-15 - Published: 2024-03-21 - Granted: 2024-12-31 - Earliest claimed: 2022-09-15 - Assignees: Sony Interactive Entertainment Inc. - Applicants: Sony Interactive Entertainment Inc. - Inventors: Brandon Sangston - Web page: https://patentgrep.com/patent/US12183352B2 ## CPC - G10L 19/008: Multichannel audio signal coding or decoding using interchannel correlation to reduce redundancy, e.g. joint-stereo, intensity-coding or matrixing - G10L 19/005: Correction of errors induced by the transmission channel, if related to the coding algorithm - H04S 3/008: {in which the audio signals are in digital form, i.e. employing more than two discrete digital channels (data reduction aspects thereof based on psychoacoustics G10L19/02)} - H04S 2400/11: Positioning of individual sound objects, e.g. moving airplane, within a sound field (H04S2420/13 takes precedence) - H04S 2420/01: Enhancing the perception of the sound image or of the spatial distribution using head related transfer functions [HRTF's] or equivalents thereof, e.g. interaural time difference [ITD] or interaural level difference [ILD] - H04S 2420/11: Application of ambisonics in stereophonic audio systems - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING - H04S: STEREOPHONIC SYSTEMS ## Abstract Ambisonics audio such as may be used for computer simulations such as computer games is improved by using multi-order optimizations that frame an optimization problem that minimizes a cost function across a subset of Ambisonics orders for a chosen Ambisonics order “N”. In a simple form, this cost function minimizes error across all orders (0<=n<=N), and additional weighting is applied to emphasize or de-emphasize particular orders. The cost functions and optimization criteria may be different for binaural and speaker outputs. ## Claims ### Claim 1 An apparatus comprising: at least one processor configured with instructions which are executable to: receive Ambisonics audio comprising at least two soundfields of different orders; identify at least one optimization function; apply at least one cost function to the optimization function to optimize at least one error over the at least two soundfields in a single spatial window of the Ambisonics audio, the cost function comprising at least one weighting vector to emphasize or de-emphasize at least one of the orders; and based at least in part on at least one output of the cost function, generate audio signals for play on at least one speaker. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the error comprises at least one error vector. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the optimization function comprises a Broyden-Fletcher-Goldfarb-Shanno (BFGS) function. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein the optimization function comprises a Sequential Least Squares Programming (SLSQP) function. ### Claim 5 (depends on 1) The apparatus of claim 1, wherein the optimization function comprises a trust-region function. ### Claim 6 (depends on 1) The apparatus of claim 1, wherein the optimization function comprises a quasi-newton function. ### Claim 7 (depends on 1) The apparatus of claim 1, wherein the optimization function comprises a neural-network. ### Claim 8 (depends on 1) The apparatus of claim 1, wherein the cost function is agnostic of a decoder configured to decode the audio signals. ### Claim 9 (depends on 8) The apparatus of claim 8, wherein the cost function comprises metrics derived from an Ambisonics encoding function. ### Claim 10 (depends on 9) The apparatus of claim 9, wherein the cost function comprises maximizing an energy vector across at least two orders. ### Claim 11 (depends on 9) The apparatus of claim 9, wherein the cost function comprises minimizing apparent-source width. ### Claim 12 (depends on 9) The apparatus of claim 9, wherein the cost function comprises minimizing frequency-dependent error. ### Claim 13 (depends on 1) The apparatus of claim 1, wherein the cost function is dependent on a decoder configured to decode the audio signals. ### Claim 14 (depends on 13) The apparatus of claim 13, wherein the cost function comprises minimizing error from the decoder by comparing output of the decoder against a reference. ### Claim 15 (depends on 1) The apparatus of claim 1, wherein the cost function calculates frequency space error metrics. ### Claim 16 (depends on 1) The apparatus of claim 1, wherein the instructions are executable to configure the audio signals for play on a Binaural system at least in part by minimizing an error metric against at least one Head-Related Transfer Function (HRTF). ### Claim 17 (depends on 1) The apparatus of claim 1, wherein the instructions are executable to configure the audio signals for play on a speaker system comprising more than two speakers at least in part by minimizing an error metric against a direct speaker signal or point-source amplitude panning algorithm. ### Claim 18 (depends on 17) The apparatus of claim 17, wherein the panning algorithm comprises a vector-based amplitude panning algorithm. ### Claim 19 A method for computing an Ambisonics spatial window that is optimized for a head-related transfer function (HRTF) comprising: optimizing the Ambisonics spatial window across at least two orders; using an optimization function, minimizing a magnitude of an error vector created by at least one cost function against the HRTF across the at least two orders to return the Ambisonics spatial window; and using the Ambisonics spatial window to play audio on at least one speaker. ### Claim 20 A decoder assembly comprising: circuitry configured to: receive Ambisonics audio comprising at least two soundfields of different orders; apply at least one cost function to an optimization function to optimize at least one error over the at least two soundfields in a single spatial window of the Ambisonics audio, the cost function comprising at least one weighting vector; and based at least in part on at least one output of the cost function, generate audio signals for play on at least one speaker.