In some embodiments, a method, apparatus and computer program for reducing noise from an audio signal captured by a drone (e.g., canceling the noise signature of a drone from the audio signal) using a model of noise emitted by the drone's propulsion system set, where the propulsion system set includes one or more propulsion systems, each of the propulsion systems including an electric motor, and wherein the noise reduction is performed in response to voltage data indicative of instantaneous voltage supplied to each electric motor of the propulsion system set. In some other embodiments, a method, apparatus and computer program for generating a noise model by determining the noise signature of at least one drone based upon a database of noise signals corresponding to at least one propulsion system and canceling the noise signature of the drone in an audio signal based upon the noise model.

Personal audio systems and methods are disclosed. A personal audio system includes a voice activity detector to determine whether or not an ambient audio stream contains voice activity, a pitch estimator to determine a frequency of a fundamental component of an annoyance noise contained in the ambient audio stream, and a filter bank to attenuate the fundamental component and at least one harmonic component of the annoyance noise to generate a personal audio stream. The filter bank implements a first filter function when the ambient audio stream does not contain voice activity, or a second filter function when the ambient audio stream contains voice activity.

A command processing device and method are provided. The command processing device includes a receiving device and a processing device. The receiving device receives an audio signal from an electronic device, wherein the audio data includes data signals and clock signals, and the data signals correspond to a first sound channel and the clock signals correspond to a second sound channel. The processing device is coupled to the receiving device. The processing device obtains the data signals from the first sound channel, and obtains the clock signals from the second sound channel. The processing device obtains one or more commands according to the data signals and clock signals, and performs operations corresponding to the commands.

This disclosure generally relates to a system, apparatus, and method for achieving an adaptive vehicle state-based hands free noise reduction feature. A noise reduction tool is provided for adaptively applying a noise reduction strategy on a sound input that uses feedback speech quality measures and machine learning to develop future noise reduction strategies, where the noise reduction strategies include analyzing vehicle operational state information and external information that are predicted to contribute to cabin noise and selecting noise reducing pre-filter options based on the analysis.

Various embodiments of the present invention relate to an electronic device and method for cancelling (or suppressing) a noise of an audio signal of an unmanned aerial vehicle, the electronic device comprising: a movement module comprising a motor; an audio module comprising a first noise suppression module; a memory module for storing control data corresponding to driving data (round per minute RPM) of the motor; and a processor functionally coupled to the audio module, the movement module and the memory module, wherein the processor sets control data according to the driving data of the motor, and applies the set control data to the audio module so that the first noise suppression module suppresses or cancels a noise in an audio signal inputted to the audio module based on the control data. Other embodiments are also applicable.

An apparatus and method for reducing background noise captured by a UAV acoustic sensor are disclosed. The background noise may be reduced by incorporating a known UAV acoustic signature corresponding to a determined flight parameter into an adaptive filter coupled to the acoustic sensor.

Methods, systems, and apparatus for audio noise reduction from a drone are disclosed. An example apparatus includes an acoustic sensor to gather acoustic data and at least one rotational motion sensor to gather rotational motion data of a first rotor and second rotational motion data of a second rotor. The example apparatus also includes an analyzer to identify a first filter that matches the first rotational motion data and identify a second filter that matches the second rotational motion data. The analyzer also is to filter the acoustic data into filtered acoustic data with the first identified filter and the second identified filter and generate an audio signal based on the filtered acoustic data.

Example techniques involve systems with multiple acoustic echo cancellers. An example implementation captures first audio within an acoustic environment and detecting, within the captured first audio content, a wake-word. In response to the wake-word and before playing an acknowledgement tone, the implementation activates (a) a first sound canceller when one or more speakers are playing back audio content or (b) a second sound canceller when the one or more speakers are idle. In response to the wake-word and after activating either (a) the first sound canceller or (b) the second sound canceller, the implementation outputs the acknowledgement tone via the one or more speakers. The implementation captures second audio within the acoustic environment and cancelling the acoustic echo of the acknowledgement tone from the captured second audio using the activated sound canceller.

Methods, systems, and apparatus for audio noise reduction from a drone are disclosed. An example apparatus includes a first sensor to gather acoustic data and a second sensor to gather rotational motion data of a rotor. The example apparatus also includes an analyzer to match the rotational motion data to a filter and filter the acoustic data using the filter. The analyzer also is to generate an audio signal based on the filtered acoustic data.

Suppression of tapping noise caused by tapping an acoustically coupled touchscreen. When a tapping event is detected on the touchscreen, a tapping noise suppressor is alerted of the event, and responds by at least temporarily mitigating the tapping noise in the audio stream. The suppression occurs temporarily for at least part of the duration of surge in audio levels that occurs as a result of the tapping event, and in a manner that reduces the psychoacoustic impact on the conversation. Suppression may be performed by first placing the tapping noise suppressors in an alert mode when a tapping event occurs. The tapping noise suppressor then monitors the audio stream generated by the microphone for the beginning of the tapping eventwhich will be represented in the form of a surge in volume. The tapping noise suppressor then temporarily applies the suppression window.