A device for masking noise, the device comprising: a transducer unit for detecting noise to be masked; a sound generating unit for generating a masking sound; a sensor unit for monitoring a user's brain activity; a controller adapted to: during a calibration, determine the user's brain activity, measured by the sensor unit, in response to a calibration sound, generated by the sound generating unit; and during use of the device, adjust signal characteristics of the masking sound based on: the noise detected by the transducer unit; the user's brain activity in response to the noise detected by the transducer unit; and the user's brain activity in response to the calibration sound generated by the sound generating unit during the calibration; a memory storage unit, in communication with the controller, adapted to store noise data based on the noise detected by the transducer unit; and characterized in that the controller is further adapted to: analyze the noise data using an algorithm, preferably wherein the algorithm is a machine-learning algorithm; determine an expected noise trend; and adjust the signal characteristics of the masking sound based on the expected noise trend. a transducer unit for detecting noise to be masked; a sound generating unit for generating a masking sound; a sensor unit for monitoring a user's brain activity; a controller adapted to: during a calibration, determine the user's brain activity, measured by the sensor unit, in response to a calibration sound, generated by the sound generating unit; and during use of the device, adjust signal characteristics of the masking sound based on: the noise detected by the transducer unit; the user's brain activity in response to the noise detected by the transducer unit; and the user's brain activity in response to the calibration sound generated by the sound generating unit during the calibration; during a calibration, determine the user's brain activity, measured by the sensor unit, in response to a calibration sound, generated by the sound generating unit; and during use of the device, adjust signal characteristics of the masking sound based on: the noise detected by the transducer unit; the user's brain activity in response to the noise detected by the transducer unit; and the user's brain activity in response to the calibration sound generated by the sound generating unit during the calibration; the noise detected by the transducer unit; the user's brain activity in response to the noise detected by the transducer unit; and the user's brain activity in response to the calibration sound generated by the sound generating unit during the calibration; a memory storage unit, in communication with the controller, adapted to store noise data based on the noise detected by the transducer unit; and characterized in that the controller is further adapted to: analyze the noise data using an algorithm, preferably wherein the algorithm is a machine-learning algorithm; determine an expected noise trend; and adjust the signal characteristics of the masking sound based on the expected noise trend. analyze the noise data using an algorithm, preferably wherein the algorithm is a machine-learning algorithm; determine an expected noise trend; and adjust the signal characteristics of the masking sound based on the expected noise trend.