For a multiple microphone system, a phase response mismatch may be corrected. One embodiment includes receiving audio from a first microphone and from a second microphone, the microphones being coupled to a single device for combining the received audio, recording the received audio from the first microphone and the second microphone before combining the received audio, detecting a phase response mismatch in the recording at the device between the audio received at the second microphone and the audio received at the first microphone, if a phase response mismatch is detected, then estimating a phase delay between the second microphone and the first microphone, and storing the estimated phase delay for use in correcting the phase delay in received audio before combining the received audio.

Focusing sound signals in a shared 3D space uses an array of physical microphones, preferably disposed evenly across a room to provide even sound coverage throughout the room. At least one processor coupled to the physical microphones does not form beams, but instead preferably forms 1000's of virtual microphone bubbles within the room. By determining the processing gains of the sound signals sourced at each of the bubbles, the location(s) of the sound source(s) in the room can be determined. This system provides not only sound improvement by focusing on the sound source(s), but with the advantage that a desired sound source can be focused on more effectively (rather than steered to) while un-focusing undesired sound sources (like reverb and noise) instead of rejecting out of beam signals. This provides a full three dimensional location and a more natural presentation of each sound within the room.

Systems and methods for optimizing voice detection via a network microphone device are disclosed herein. In one example, individual microphones of a network microphone device detect sound. The sound data is captured in a first buffer and analyzed to detect a trigger event. Metadata associated with the sound data is captured in a second buffer and provided to at least one network device to determine at least one characteristic of the detected sound based on the metadata. The network device provides a response that includes an instruction, based on the determined characteristic, to modify at least one performance parameter of the NMD. The NMD then modifies the at least one performance parameter based on the instruction.

Audio apparatus includes a neckband, which is sized and shaped to be worn around a neck of a human subject and includes left and right sides that rest respectively above the left and right clavicles of the human subject wearing the neckband. First and second arrays of microphones are disposed respectively on the left and right sides of the neckband and configured to produce respective electrical signals in response to acoustical inputs to the microphones. One or more earphones are worn in the ears of the human subject. Processing circuitry is coupled to receive and mix the electrical signals from the microphones in the first and second arrays in accordance with a specified directional response relative to the neckband so as to generate a combined audio signal for output via the one or more earphones.

The present invention provides an acoustic characteristic calibration method superior in at least one of improved repeatability of an inspection state, a reduced influence of a noise in calibrating an acoustic characteristic, and a reduced load in FFT arithmetic processing. A reference acoustic signal is output from a sound output unit (10) and input to a sound input unit (20) of a vehicle inspection device (2). The signal input to the sound input unit (20) is subjected to A/D conversion, and then the FFT arithmetic processing is carried out thereby to detect the frequency response characteristic of the sound input unit (20). The frequency response characteristic of the sound input unit (20) and the frequency characteristic of the reference acoustic signal are compared to determine the correction factor at each frequency. Based on the correction factor, the frequency response characteristic of the sound input unit (20) is calibrated.

A sound pickup method obtains a correlation between a first sound pickup signal of a directional first microphone and a second sound pickup signal of a non-directional second microphone, and performs level control of the first sound pickup signal or the second sound pickup signal according to a calculation result of the correlation.

A hearing device, e.g. a hearing aid, comprises first and second separate, interconnectable parts comprising first and second input transducers, respectively, for providing first and second electric input signals, respectively, representative of sound in an environment of the user, and a beamformer filtering unit configured to provide a spatially filtered signal based thereon, and a memory comprising a previously determined own voice transfer function corresponding to a target sound source located at said user's mouth. The hearing device is configured to determine an updated own voice transfer function according to activation of a predefined trigger, when the user's own voice is present, and to store an updated own voice transfer function in said memory. The hearing device further comprises at least one combination unit configured to apply a first multiplication factor to at least one of the first and second electric input signals, and a control unit configured to determine the first multiplication factor so as to decrease, e.g. minimize a difference measure representative of a difference between the previously determined own voice transfer function and the updated own voice transfer function.

A method for auralizing a multi-microphone device. Path information for one or more sound paths using dimensions and room reflection coefficients of a simulated room for one of a plurality of microphones included in a multi-microphone device is determined. An array-related transfer functions (ARTFs) for the one of the plurality of microphones is retrieved. The auralized impulse response for the one of the plurality of microphones is generated based at least on the retrieved ARTFs and the determined path information.

Method and systems are provided for interpreting speech data. A method and system for recognizing speech involving a filter module to generate a set of processed audio data based on raw audio data; a translation module to provide a set of translation results for the raw audio data; and a decision module to select the text data that represents the raw audio data. A method for minimizing noise in audio signals received by a microphone array is also described. A method and system of automatic entry of data into one or more data fields involving receiving a processed audio data; and operating a processing module to: search in a trigger dictionary for a field identifier that corresponds to the trigger identifier; identify a data field associated with a data field identifier corresponding to the field identifier; and providing content data associated with the trigger identifier to the identified data field.

Embodiments described herein provide a combined multi-source time difference of arrival (TDOA) tracking and voice activity detection (VAD) mechanism that is applicable for generic array geometries, e.g., a microphone array that lies on a plane. The combined multi-source TDOA tracking and VAD mechanism scans the azimuth and elevation angles of the microphone array in microphone pairs, based on which a planar locus of physically admissible TDOAs can be formed in the multi-dimensional TDOA space of multiple microphone pairs. In this way, the multi-dimensional TDOA tracking reduces the number of calculations that was usually involved in traditional TDOA by performing the TDOA search for each dimension separately.