A method for feedforward noise cancellation in an enclosed space within a structure is provided. The method comprises placing a microphone array inside an inner surface of the enclosed space and conducting modal testing on an outside surface of the enclosed space, wherein the modal testing comprises multiple incoherent noise sources corresponding to locations of microphones in the microphone array. Noise generated by the modal testing is processed to create a number of acoustic mathematical models of the enclosed space. In response to incoherent noise within the enclosed space, a noise canceling signal is generated according to an output of the mathematical models.

Examples of system for ambient aversive sound detection, identification and management are described. The system comprises an earpiece device with a microphone configured to capture ambient sound around a user and sample it into small segments of the ambient sound, a speaker and a regulator to regulate the ambient sound segment transmitted to the speaker. The system further comprises a processing unit that identifies aversive ambient sound signals in the captured sound segment and provide recommendation action to manage the aversive sound signal by removing, supressing, attenuating or masking the aversive signals.

An urban air mobility (UAM) noise reduction system and method are provided, where the UAM noise reduction system includes a UAM configured to detect and to provide rotation per minute (RPM) information of a propeller and location coordinate information, and a noise canceling device configured to predict a noise canceling sound wave amplitude on the basis of the RPM information of the propeller and the location coordinate information received through the UAM and to output a noise canceling sound wave corresponding to the predicted noise canceling sound wave amplitude to the UAM.

The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise. The present disclosure enhances the applicability of feedback active noise control in practical applications.

An apparatus for operating a noise suppression unit of a vehicle includes a control unit. The control unit is configured to reduce interfering noise in or on the vehicle by generating at least one acoustic compensation signal. The control unit is also configured to determine noise information relating to expected interfering noise, including an expected level of interfering noise, at an upcoming vehicle position while the vehicle is traveling. The control unit is also configured to cause the noise suppression unit to be activated or to be in an energy-saving mode at the upcoming vehicle position, depending on the noise information obtained.

Embodiments of the present disclosure disclose an earphone including a fixing structure, a first microphone array, a processor, and a speaker. The fixing structure is configured to fix the earphone near a user's ear without blocking the user's ear canal and including a hook-shaped component and a body part. The first microphone array is located in the body part and is configured to pick up environmental noise. The processor is located in the hook-shaped component or the body part and is configured to estimate a sound field at a target spatial position using the first microphone array and generate a noise reduction signal based on the estimated sound field. The target spatial position is closer to the user's ear canal than any microphone in the first microphone array. The speaker is located in the body part and is configured to output a target signal according to the noise reduction signal.

For example, a controller of an Active Acoustic Control (AAC) system may be configured to process input information, the input information including AAC configuration information corresponding to a configuration of AAC in a sound control zone; a plurality of noise inputs representing acoustic noise at a plurality of noise sensing locations; and a plurality of residual-noise inputs representing acoustic residual-noise at a plurality of residual-noise sensing locations within the sound control zone. For example, the controller may determine a sound control pattern to control sound within the sound control zone based on the AAC configuration information, the plurality of noise inputs, and the plurality of residual-noise inputs. For example, the controller may output the sound control pattern to a plurality of acoustic transducers.

A signal processing apparatus is configured to preprocess a sound wave signal and output a processed audio signal through an electromagnetic wave. The signal processing apparatus includes: a receiving unit, configured to receive at least one sound wave signal; a conversion unit, configured to convert the at least one sound wave signal to at least one audio signal; a positioning unit, configured to determine position information related to the at least one sound wave signal; a processing unit, configured to determine a sending time point of at least one audio signal based on the position information and a first time point, where the first time point is a time point at which the receiving unit receives the at least one sound wave signal; and a sending unit, configured to send the at least one audio signal through the electromagnetic wave.

The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise. The present disclosure enhances the applicability of feedback active noise control in practical applications.

An urban air mobility (UAM) noise reduction system and method are provided, where the UAM noise reduction system includes a UAM configured to detect and to provide rotation per minute (RPM) information of a propeller and location coordinate information, and a noise canceling device configured to predict a noise canceling sound wave amplitude on the basis of the RPM information of the propeller and the location coordinate information received through the UAM and to output a noise canceling sound wave corresponding to the predicted noise canceling sound wave amplitude to the UAM.