A headset for acoustic authentication of a user is provided, the headset comprising at least a first microphone, a second microphone, a controllable filter, and an authenticator. The first microphone is arranged to obtain a first input signal. The second microphone is arranged to obtain a second input signal. The controllable filter is configured to receive the first input signal and the second input signal and to determine at least one filter transfer function from the received first input signal and the second input signal. The authenticator is configured to determine a current user acoustic signature from the at least one filter transfer function and to compare the current user acoustic signature with a predefined user acoustic signature and to authenticate the user based on the comparison of the current user acoustic signature with the predefined user acoustic signature.

An audio device comprising an interface, memory, and a processor is disclosed. A first microphone input signal and a second microphone input signal is processed for provision of an output audio signal; and output the output audio signal, wherein to process the microphone signals determine a first distractor indicator based on features associated with the input signals; determine a first distractor attenuation parameter based on the first distractor indicator; determine a second distractor indicator based on one or more features associated with the first microphone input signal and the second microphone input signal; determine a second distractor attenuation parameter based on the second distractor indicator; determine an attenuator gain based on the first distractor attenuation parameter and the second gain compensation parameter; and apply a noise suppression scheme to a first beamforming output signal according to the attenuator gain for provision of the output audio signal.

Systems and methods for enhancing a headset user's own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

In some aspects, an edge appliance is placed in an active mode and causes a software agent that is based on a machine learning algorithm to engage in a conversation to take an order from a customer that is located at an order post. The edge appliance provides, using a communication interface, audio data that includes the conversation, to a communications system of a restaurant. The edge appliance provides, using the communication interface, a content of a cart associated with the order to a point-of-sale terminal of the restaurant. If the edge appliance determines, using the communication interface, that a microphone of the communication system is receiving audio input from an employee, the edge appliance automatically transitions the edge appliance from the active mode to an override mode, enabling the employee to receive a remainder of the order from the customer.

A communication system with a noise cancellation (NC) assembly providing adaptive or dynamic noise cancellation. The NC assembly includes a localizer module determining, during a communication session (active speaking or during idle times), a location of the active talker. The NC assembly includes a beam generator forming a beam in the determined direction of the active talker to enhance the active talker speech. Once the NC assembly has determined the position of the active talker, the NC assembly assigns a microphone of the microphone array or generated beam in that active direction to be the “active signal” source. The NC assembly assigns a second microphone or beam to be the noise source for NC purposes, and this source may be selected to be in acoustic shadow of the first microphone used as the active signal source or may be the farthest away in its position from the active talker's position.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

Communication terminal includes a first microphone system, a second microphone system, and a noise reduction processing unit (NRPU). The NRPU receives a primary signal from the first microphone system and a secondary signal from the second microphone system. The NRPU dynamically identify an optimal transfer function of a correction filter which can be applied to the secondary signal provided by the second microphone system to obtain a correction signal. The correction signal is subtracted from the primary signal to obtain a remainder signal which approximates a signal of interest contained within the primary signal.

A first noise level, which is an estimated value of a magnitude of a noise component included in a first sound collection signal obtained from a first microphone which collects sound emitted from a first sound collection and amplification position is obtained, a second noise level, which is an estimated value of a magnitude of a noise component included in a second sound collection signal obtained from a second microphone which collects sound emitted from a second sound collection and amplification position is obtained, a ratio of a reproduced noisy sound level, which is an estimated value of a magnitude of noise at a position of a passenger at the second sound collection and amplification position in a case where the first noise level is reproduced from a second speaker placed at the second sound collection and amplification position, with respect to a second noisy sound level, which is an estimated value of a magnitude of noise corresponding to the second noise level at the position of the passenger at the second sound collection and amplification position is obtained, and a noise suppression amount is obtained so that a product of this ratio and the noise suppression amount becomes a constant set in advance.

Examples of systems and methods for audio transcription are described. Audio data may be obtained from multiple recording devices at or near a scene. Audio data from multiple recording devices may be used to generate a final transcription. For example, when transcribing audio data from one recording device, audio data from another recording device may be used to generate the final transcript. The data from the second recording device may be used when it is determined that the recording devices were in proximity at the time the relevant portions of audio data were recorded and/or when a portion of the audio from the second recording device is verified to correspond with a portion of the audio from the first recording device. In some examples, data from the second recording device may be used when data from the first recording device is determined to be of low quality.

A method of noise reduction, which is applied to an electronic device. The electronic device includes a first sound collector and a second sound collector, installation positions of the first sound collector and the second sound collectors are different; the method includes: determining a desired sound signal and an interference sound signal based on a first sound signal collected by the first sound collector and a second sound signal collected by the second sound collector (S102); obtaining a third sound signal by performing coherent noise elimination processing on the desired sound signal based on the interfering sound signal (S103); and then obtaining a target sound signal by performing incoherent noise suppression processing on the third sound signal based on a probability of existence of a speech in the third sound signal (S104).