An audio signal processing device includes a sound acquisition unit configured to acquire audio data generated by collecting a sound in a sound collection target space, a selection unit configured to select, based on a priority of each of a plurality of areas in the sound collection target space, one or more of the areas in the sound collection target space, and an output unit configured to output processed data, for which predetermined signal processing for the areas selected by the selection unit is executed on the audio data acquired by the sound acquisition unit, and the predetermined signal processing for an area not selected by the selection unit is not executed on the audio data.

An audio signal processing device includes a sound acquisition unit configured to acquire audio data generated by collecting a sound in a sound collection target space, a selection unit configured to select, based on a priority of each of a plurality of areas in the sound collection target space, one or more of the areas in the sound collection target space, and an output unit configured to output processed data, for which predetermined signal processing for the areas selected by the selection unit is executed on the audio data acquired by the sound acquisition unit, and the predetermined signal processing for an area not selected by the selection unit is not executed on the audio data.

The present application discloses an apparatus for controlling an earphone and a media player in communication with the earphone, including an ambient sound detector configured to detect an ambient sound volume level; a processor configured to select an adjustment value to be applied to an audio volume level to be produced by an earphone speaker of the earphone based on the ambient sound volume level; and a controller configured to adjust the audio volume level of the earphone speaker based on the adjustment value selected by the processor.

A circuit and method is disclosed for filtering an audio signal. The circuit has a first quadrature source and multipliers for multiplying the input signal by the I and Q outputs of the quadrature source. The multiplied inputs are then passed through a pair of low pass filters, which may have an adjustable Q factor. The outputs of the low pass filters are then multiplied in a second pair of multipliers by the I and Q outputs, respectively, of a second quadrature source, which will typically be of the same frequency, but different amplitude and phase, of the first quadrature source. The twice-multiplied signals are then summed by an adder to provide an output signal. The circuit may be modified to include a companding circuit between the low pass filters and the second pair of multipliers that determines the amplitude of the input signal, filters it, and compands the signal in a compandor. The compandor may have adjustable parameters. The circuit thus allows for far greater flexibility and control of the processing of the input signal than prior art circuits.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user’s voice, storing the user’s voice in a memory of an earpiece device, or storing the user’s voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user’s voice, storing the user’s voice in a memory of an earpiece device, or storing the user’s voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

An adaptive music system includes at least one processing circuit operative to characterize ambient noise features of digitized ambient noise obtained from a microphone circuit associated with a user device and characterizes music features of digitized music being played through the user device to a speaker. The at least one processing circuit is further operative to generate a music playout command responsive to processing the characterized ambient noise features and the characterized music features through a machine learning model that has been trained based on a combination of historical user actions to control music playout, historically characterized ambient noise features that are correlated in time to the historical user actions, and historically characterized music features that are correlated in time to the historical user actions. The at least one processing circuit is further operative to control music playout through the user device responsive to the music playout command.

An adaptive music system includes at least one processing circuit operative to characterize ambient noise features of digitized ambient noise obtained from a microphone circuit associated with a user device and characterizes music features of digitized music being played through the user device to a speaker. The at least one processing circuit is further operative to generate a music playout command responsive to processing the characterized ambient noise features and the characterized music features through a machine learning model that has been trained based on a combination of historical user actions to control music playout, historically characterized ambient noise features that are correlated in time to the historical user actions, and historically characterized music features that are correlated in time to the historical user actions. The at least one processing circuit is further operative to control music playout through the user device responsive to the music playout command.

Systems and methods for automatically adjusting device volume based on learned volume preferences are disclosed herein. A first device receives a wireless signal from a second device. A signal strength of the wireless signal is determined, and a location of the second device is determined based on the signal strength of the wireless signal. Historical volume level data for the first device is retrieved from memory. A target volume level for the first device is determined based on the location of the second device and the historical volume level data. A volume setting of the first device is automatically adjusted to the target volume level.

Systems and methods for automatically adjusting device volume based on learned volume preferences are disclosed herein. A first device receives a wireless signal from a second device. A signal strength of the wireless signal is determined, and a location of the second device is determined based on the signal strength of the wireless signal. Historical volume level data for the first device is retrieved from memory. A target volume level for the first device is determined based on the location of the second device and the historical volume level data. A volume setting of the first device is automatically adjusted to the target volume level.