An ear interface mode of headphones may be determined by measuring an acoustic response of the headphones. For example, the headphones may be determined to be in a leaky or sealed configuration. An adaptive noise cancellation (ANC) system may be controlled based on the determined ear interface mode of the headphones. For example, a set of configuration parameters may be loaded for the ANC system corresponding to the known ear interface mode. An anti-noise signal may be generated according to the selected configuration parameters, and that anti-noise signal added during playback of media, such as voice recordings, music, videos, or telephone call speech.

A self tuned apparatus (100) for active noise control includes a first transducer (105) and a second transducer (110), a noise controlling module (115), a power amplifier (120) and a first loudspeaker (125) and a second loudspeaker (130) coupled to the power amplifier (120). The noise controlling module (115) is coupled to the first transducer (105) and the second transducer (110). The power amplifier (120) is coupled to the noise controlling module (115). Particularly, the noise controlling module (115) employs at least one control algorithm.

An intelligent active noise control device according to an embodiment includes a microphone mounted in a vehicle and receiving in-vehicle noise, a noise of interest model configurer generating a noise of interest model by being trained on noise characteristics according to a preset type of noise, a similarity analysis and decision unit analyzing collected noise by comparing the collected noise with the noise model of interest, an active noise control area configurer setting an active noise control area according to an analyzed similarity, and an active noise control sound output unit outputting an active noise control sound to the set active noise control area.

A computer-implemented method for generating crosstalk cancellation (CTC) filters for a reverberant acoustic environment having multiple audio zones, the method comprising determining, based on a CTC simulation model of an acoustic environment, a first set of frequency responses for respective positions proximate to one or more speakers located in the acoustic environment, and a second set of frequency responses for respective listening positions in the acoustic environment, generating, based on the first set of frequency responses and the second set of frequency responses, an acoustic environment transfer function matrix for the acoustic environment, and generating, based on the acoustic environment transfer function matrix, a set of CTC filters for a set of speakers in the acoustic environment.

Ambient sound is converted into digital signals. A processor performs active noise cancellation and/or a transformation operation that is distinct from the active noise cancellation on the digital signals. The active noise cancellation and the transformation operation transform the digital signals into modified digital signals. The modified digital signals are converted into modified analog signals. The modified analog signals are outputted as audio waves. An interior microphone is configured to output an output signal to the processor in response to receiving the modified analog signals. In response to receiving the output signal from the interior microphone, the processor is configured to determine whether the modified digital signals produce desired audio waves.

Various implementations include a method of training a road noise cancelation (RNC) system for a vehicle, including: providing inputs to RNC system, the inputs obtained from: a set of ear-mounted microphones on a user, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, the inputs from the set of ear-mounted microphones on the user approximating a signal detected by the ears of the user; adapting a set of parameters in the RNC system defining an estimated signal detected at respective ears of the user based on the inputs; and generating at least one of the following for input during an operating mode of the RNC system: estimated ear microphone signals based on the adapted set of parameters, or a set of projection filters for use in determining an estimated ear signal at the respective ears of the user.

In at least one embodiment, an active noise cancellation (ANC) system is provided. The system includes at least one audio signal source, at least one loudspeaker, at least one microphone, and at least one controller. The at least one controller is programmed to receive a first error signal and a second error signal and to provide an estimated impulse response based at least on the first error signal and the second error signal. The at least one controller is programmed to select a first pre-stored impulse response from a plurality of pre-stored impulse responses based on the estimated impulse response to filter one or more reference signals at an adaptive filter to generate the anti-noise signal and to select a first plurality of pre-stored tuning parameters from a plurality of pre-stored sets of the tuning parameters based on the first pre-stored impulse response.

In accordance with systems and methods of the present disclosure, an adaptive noise cancellation system may include an alignment filter configured to correct misalignment of a reference microphone signal and an error microphone signal by generating a misalignment correction signal.

In accordance with systems and methods of the present disclosure, an adaptive noise cancellation system may include an alignment filter configured to correct misalignment of a reference microphone signal and an error microphone signal by generating a misalignment correction signal.

An earpiece for real-time audio processing of ambient sound includes an ear bud that provides passive noise attenuation to the earpiece such that exterior ambient sound is substantially reduced within an ear of a wearer, an exterior microphone that receives ambient sound and converts the received ambient sound into analog electrical signals, and an analog-to-digital converter that converts the analog electrical signals into digital signals representative of the ambient sounds. The earpiece further includes a digital signal processor that performs a transformation operation on the digital signals according to instructions received from a mobile device, the transformation operation transforms the digital signals into modified digital signals, a digital-to-analog converter that converts the modified digital signals into modified analog electrical signals, and a speaker that outputs the modified analog electrical signals as audio waves.