An angle of arrival estimation method and device, where a first device: collects a first signal from a second device using a reference antenna and a first antenna group; determines first channel state information (CSI); collects a second signal from the second device using the reference antenna and a second antenna group; determines second CSI; determines a phase difference vector between the first signal and the second signal based on a vector corresponding to the reference antenna in the first CSI and a vector corresponding to the reference antenna in the second CSI; compensates for the second CSI using the phase difference vector; and estimates an angle of arrival of the second device based on the first CSI and compensated second CSI.

A directional receiver system may include a receiver, a plurality of receive antenna elements, and a circuit. The receiver may include an input port and an output. The plurality of receive antenna elements may be fixedly configured into a known geometric relationship to each other, and each of the receive antenna elements may be connected to the input port of the receiver. The circuit may be coupled to the output of the receiver, configured to determine time differences at which signals from a source are incident upon the antenna elements, and configured to determine an angular orientation of the source to the receive antenna elements based on the time differences.

Provided are a detection method for a sound source and a detection device therefor, which are capable of accurately detecting the position of a sound source through use of measurement results of sound intensities. In the detection method, I.sub.all=(I.sub.x.sup.2+I.sub.y.sup.2+I.sub.z.sup.2), which is a total value of the sound intensities I.sub.x, I.sub.y, and I.sub.z in three axial directions (x-, y-, and z-axis directions) orthogonal to each other at a sound receiving point (P) in a sound field, is calculated, and then the position of the sound source is estimated after extracting the sound source by performing processing with averaged values within a predetermined peak width instead of the magnitude of a peak in a sound intensity waveform of the total value, or the position of the sound source is estimated after extracting the sound source with attention being given to a spatial travel speed of a sound intensity or a sound particle velocity of the total value.

Aspects of the present invention disclose a method for preventing adversarial audio attacks through detecting and isolating inconsistencies utilizing beamforming techniques and IoT devices. The method includes one or more processors identifying an audio command received by a listening device. The method further includes determining a source location of the audio command utilizing a sensor array of the listening device. The method further includes determining a location of a user in relation to the listening device based on data of an Internet of Things (IoT) device. The method further includes determining an inconsistency between the determines source location and the determined location of the user based at least in part on data of the sensor array and data of the IoT device.

A system is described that comprises a plurality of sensor nodes and at least one remote server, wherein each sensor node of the plurality of sensor nodes and the at least one remote server are communicatively coupled, wherein the plurality of sensor nodes receive at least one acoustic signal, process the at least one acoustic signal to detect one or more transient events, classify the one or more transient events as an event type, and determine geometry information and timing information of the one or more transient events. The system comprises at least one of the plurality of sensor nodes and the at least one remote server identifying the source of the one or more transient events.

A system is described that comprises a plurality of sensor nodes and at least one remote server, wherein each sensor node of the plurality of sensor nodes and the at least one remote server are communicatively coupled, wherein the plurality of sensor nodes receive at least one acoustic signal, process the at least one acoustic signal to detect one or more transient events, classify the one or more transient events as an event type, and determine geometry information and timing information of the one or more transient events. The system comprises at least one of the plurality of sensor nodes and the at least one remote server identifying the source of the one or more transient events.

A first intelligent assistant computing device configured to receive and respond to natural language inputs provided by human users syncs to a reference clock of a wireless computer network. The first intelligent assistant computing device receives a communication sent by a second intelligent assistant computing device indicating a signal emission time at which the second intelligent assistant computing device emitted a position calibration signal. The first intelligent assistant computing device records a signal detection time at which the position calibration signal was detected. Based on a difference between 1) the signal emission time and the signal detection time, and 2) a known propagation speed of the position calibration signal, a distance between the first and second intelligent assistant computing devices is calculated.

A first intelligent assistant computing device configured to receive and respond to natural language inputs provided by human users syncs to a reference clock of a wireless computer network. The first intelligent assistant computing device receives a communication sent by a second intelligent assistant computing device indicating a signal emission time at which the second intelligent assistant computing device emitted a position calibration signal. The first intelligent assistant computing device records a signal detection time at which the position calibration signal was detected. Based on a difference between 1) the signal emission time and the signal detection time, and 2) a known propagation speed of the position calibration signal, a distance between the first and second intelligent assistant computing devices is calculated.

Provided is a sound source tracking apparatuses including a vibration unit including vibrators configured to vibrate in response to an ambient sound, the ambient sound including individual sounds, and a processor configured to separate the ambient sound into individual sounds, to determine a target individual sound having a target tone color among the individual sounds, and to obtain a relative location of a target sound source that generates the target individual sound.

Computing devices and methods for associating a semantic identifier with an object are disclosed. In one example, a three-dimensional model of an environment comprising the object is generated. Image data of the environment is sent to a user computing device for display by the user computing device. User input comprising position data of the object and the semantic identifier is received. The position data is mapped to a three-dimensional location in the three-dimensional model at which the object is located. Based at least on mapping the position data to the three-dimensional location of the object, the semantic identifier is associated with the object.