# US 12,112,734 B2 · Open active noise cancellation system > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,112,734 B2 - Document ID: US12112734B2 - Status: Granted - Kind: B2 - Application number: 17/607,002 - Filed: 2019-05-01 - Published: 2022-06-30 - Granted: 2024-10-08 - Earliest claimed: 2019-05-01 - Assignees: Harman International Industries, Incorporated - Applicants: Harman International Industries, Incorporated - Inventors: Donald Joseph Butts - Web page: https://patentgrep.com/patent/US12112734B2 ## CPC - G10K 11/17821: {characterised by the analysis of the input signals only} - G10K 11/17823: {Reference signals, e.g. ambient acoustic environment} - G10K 11/17873: {using a reference signal without an error signal, e.g. pure feedforward} - G10K 11/17881: {the reference signal being an acoustic signal, e.g. recorded with a microphone} - G10L 21/0216: characterised by the method used for estimating noise - G10K 2210/111: Directivity control or beam pattern - G10K 2210/3038: Neural networks - G10L 2021/02161: {Number of inputs available containing the signal or the noise to be suppressed} - G10K: SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING ## Abstract Embodiments of the present disclosure set forth a method of reducing noise in an audio signal. The method includes determining, based on sensor data acquired from a first set of sensors, a first position of a user in an environment. The method also includes acquiring, via the first set of sensors, one or more audio signals associated with sound in the environment and identifying one or more noise elements in the one or more audio signals. The method also includes generating a first directional audio signal based on the one or more noise elements. When the first directional audio signal is outputted by a first speaker, the first speaker produces a first acoustic field that attenuates the one or more noise elements at the first position. ## Claims ### Claim 1 A method for reducing noise in an audio signal, the method comprising: determining, based on sensor data acquired from a first set of sensors, a first position of a user in an environment; acquiring, via the first set of sensors, one or more audio signals associated with sound in the environment; identifying one or more noise elements in the one or more audio signals; identifying one or more individual speakers in the one or more audio signals by comparing, via a neural network, the one or more audio signals with learned speech elements and speaker characteristics; decomposing the one or more audio signals into one or more filtered signals, wherein each filtered signal corresponds to one or more frequency sub-bands of the one or more audio signals; and generating, based on the one or more filtered signals, a first directional audio signal wherein, when the first directional audio signal is outputted by a first loudspeaker, the first loudspeaker produces, based on the first directional audio signal, a first acoustic field that attenuates the one or more frequency sub-bands associated with the one or more noise elements at the first position and emphasizes one or more frequency sub-bands associated with the one or more individual speakers. ### Claim 2 (depends on 1) The method of claim 1, wherein identifying the one or more noise elements comprises: comparing the one or more audio signals to at least one reference signal; and when the one or more audio signals match the at least one reference signal, classifying the one or more audio signals based on the at least one reference signal. ### Claim 3 (depends on 1) The method of claim 1, wherein identifying the one or more noise elements comprises: comparing, via the neural network, a first audio signal included in the one or more audio signals to a first reference signal associated with a first noise element; and based on determining that the first audio signal matches the first reference signal, classifying the first audio signal as including the first noise element. ### Claim 4 (depends on 1) The method of claim 1, further comprising: comparing a first audio signal included in the one or more audio signals to a first set of reference signals; determining that the first audio signal does not match at least one reference signal included in the first set of reference signals; and storing data associated with the first audio signal as an additional reference signal included in the first set of reference signals. ### Claim 5 (depends on 1) The method of claim 1, where identifying the one or more noise elements comprises: comparing the one or more audio signals to each reference signal included in a first set of reference signals; and when the one or more audio signals match at least one reference signal included in the first set of reference signals, classifying the one or more audio signals as the one or more noise elements; and when the one or more audio signals do not match at least one reference signal included in the first set of reference signals, determining that the one or more audio signals will not be classified as the one or more noise elements. ### Claim 6 (depends on 1) The method of claim 1, further comprising: determining, based on sensor data acquired from the first set of sensors, a second position of the user in an environment; and generating a second directional audio signal based on the one or more noise elements, wherein, when the second directional audio signal is outputted by the first loudspeaker, the first loudspeaker produces a second acoustic field that attenuates the one or more noise elements at the second position. ### Claim 7 (depends on 1) The method of claim 1, further comprising determining a second position of the first loudspeaker, wherein the first directional audio signal is based on the first position and the second position. ### Claim 8 (depends on 1) The method of claim 1, further comprising receiving, from a second device via a first network, an input audio signal, wherein the first directional audio signal includes at least a portion of the input audio signal. ### Claim 9 (depends on 1) The method of claim 1, further comprising generating a first set of directional audio signals based on the one or more noise elements, wherein, when the first set of directional audio signals is outputted by a first plurality of loudspeakers, the first plurality of loudspeakers produce the first acoustic field. ### Claim 10 An audio system, comprising: a first set of sensors that: produces sensor data associated with a first position of a user in an environment, and produces one or more audio signals associated with sound acquired from the environment; a first loudspeaker; and a processor coupled to the first set of sensors and the first loudspeaker that: determines, based on the sensor data, the first position of the user, receives, from the first set of sensors, the one or more audio signals, identifies one or more noise elements in the one or more audio signals, identifies one or more individual speakers in the one or more audio signals by comparing, via a neural network, the one or more audio signals with learned speech elements and speaker characteristics, decomposes the one or more audio signals into one or more filtered signals, wherein each filtered signal corresponds to one or more frequency sub-bands of the one or more audio signals, and generates, based on the one or more filtered signals, a first directional audio signal wherein the first loudspeaker outputs the first directional audio signal to produce, based on the first directional audio signal, a first acoustic field that attenuates the one or more frequency sub-bands associated with the one or more noise elements at the first position and emphasizes one or more frequency sub-bands associated with the one or more individual speakers. ### Claim 11 (depends on 10) The audio system of claim 10, further comprising a first database that stores a first set of reference signals associated with the one or more noise elements. ### Claim 12 (depends on 11) The audio system of claim 11, wherein the processor further: compares the one or more audio signals to a first set of reference signals; when the one or more audio signals match at least one reference signal included in the first set of reference signals, classifies the one or more audio signals as the one or more noise elements; and when the one or more audio signals do not match at least one reference signal included in the first set of reference signals, determines that the one or more audio signals will not be classified as the one or more noise elements. ### Claim 13 (depends on 10) The audio system of claim 10, wherein the first set of sensors comprises: at least one camera that acquires position data associated with the first position; and at least one microphone that acquires the one or more audio signals. ### Claim 14 (depends on 10) The audio system of claim 10, wherein the first loudspeaker comprises a parametric loudspeaker. ### Claim 15 (depends on 10) The audio system of claim 10, wherein: the first loudspeaker is included in a plurality of parametric loudspeakers of the audio system; the processor further generates a first set of directional audio signals based on the one or more noise elements; and each parametric loudspeaker included in the plurality of parametric loudspeakers outputs at least one directional audio signal in the first set of directional audio signals to produce the first acoustic field. ### Claim 16 (depends on 10) The audio system of claim 10, wherein: the first set of sensors further produces sensor data associated with a second position of the user; the processor further: determines, based on the sensor data, the second position of the user, and generates a second directional audio signal based on the one or more noise elements; and the first loudspeaker outputs the second directional audio signal to produce a second acoustic field that attenuates the one or more noise elements at the second position. ### Claim 17 One or more non-transitory computer-readable media comprising instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of: determining a first position of a user in an environment; acquiring, via a first set of sensors, one or more audio signals associated with sound in the environment; identifying one or more noise elements in the one or more audio signals by: comparing the one or more audio signals to each reference signal included in a first set of reference signals, and when the one or more audio signals match at least one reference signal included in the first set of reference signals, classifying the one or more audio signals as the one or more noise elements; identifying one or more individual speakers in the one or more audio signals by comparing, via a neural network, the one or more audio signals with learned speech elements and speaker characteristics; decomposing the one or more audio signals into one or more filtered signals, wherein each filtered signal corresponds to one or more frequency sub-bands of the one or more audio signals; and generating, based on the one or more filtered signals, a first directional audio signal wherein, when the first directional audio signal is outputted by a first loudspeaker, the first loudspeaker produces, based on the first directional audio signal, a first acoustic field that attenuates the one or more frequency sub-bands associated with the one or more noise elements at the first position and emphasizes one or more frequency sub-bands associated with the one or more individual speakers. ### Claim 18 (depends on 17) The one or more non-transitory computer-readable media of claim 17 further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of: generating a noise cancellation signal based on the one or more noise elements by generating an anti-noise signal that matches an amplitude for the at least one reference signal and is antiphase to the at least one reference signal. ### Claim 19 (depends on 18) The one or more non-transitory computer-readable media of claim 18, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the steps of: storing the anti-noise signal; and associating the anti-noise signal with the at least one reference signal. ### Claim 20 (depends on 17) The one or more non-transitory computer-readable media of claim 17, further comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform the step of, upon determining that the one or more audio signals will not be classified as the one or more noise elements, storing data associated with the one or more audio signals as an additional reference signal included in the first set of reference signals.