A method for natural language interaction includes recording speech provided by a human user. The recorded speech is translated into a machine-readable natural language input relating to an interaction topic. An interaction timer is maintained that tracks a length of time since a last machine-readable natural language input referring to the interaction topic was translated. Based on a current value of the interaction timer being greater than an interaction engagement threshold, a message relating to the interaction topic is delivered with a first natural language phrasing that includes an interaction topic reminder. Based on the current value of the interaction timer being less than the interaction engagement threshold, the message relating to the interaction topic is delivered with a second natural language phrasing that lacks the interaction topic reminder.

An apparatus and a method for measuring distance by using electronic devices are provided. The apparatus includes an output unit, an input unit, and a controller. The output unit may be configured to transmit the first sound wave, and the input unit may be configured to receive the second sound wave from another apparatus that receives the first sound wave. The controller may be configured to determine the distance between the apparatus and the another apparatus based on a first value and a second value. The first value may correspond to a difference between a timing of initiating a transmission of the first sound wave and a timing of receiving the second sound wave, and the second value may correspond to a difference between a timing when the another apparatus initiates the transmission of the second sound wave and the timing when the another apparatus receives the first sound wave.

An apparatus and a method for measuring distance by using electronic devices are provided. The apparatus includes an output unit, an input unit, and a controller. The output unit may be configured to transmit the first sound wave, and the input unit may be configured to receive the second sound wave from another apparatus that receives the first sound wave. The controller may be configured to determine the distance between the apparatus and the another apparatus based on a first value and a second value. The first value may correspond to a difference between a timing of initiating a transmission of the first sound wave and a timing of receiving the second sound wave, and the second value may correspond to a difference between a timing when the another apparatus initiates the transmission of the second sound wave and the timing when the another apparatus receives the first sound wave.

An unmanned aircraft includes: a sensor that includes at least a microphone that generates sound data; and a processor. The processor determines quality of a target sound using the sound data generated by the microphone, obtains a positional relationship between the unmanned aircraft and a sound source of the target sound using data generated by the sensor, and controls movement of the unmanned aircraft to control a distance between the unmanned aircraft and the sound source of the target sound, in accordance with the quality of the target sound and the positional relationship.

A method, device and computer program product for controlling the device by tracking a movement of a hand or other objects. The device receives acoustic signals. At least a portion of the received signals are transformed into two-dimensional sinusoids whose frequencies are proportional to an angle-of-arrival (AoA) and a propagation distance of the reflected signals. An AoA-di stance profile is derived based on signals received from the object by evaluating frequencies of the two-dimensional sinusoids. Then, an AoA-di stance pair is derived from the AoA-di stance profile. A current location of the object is determined based on the estimated AoA-di stance pair. The device then performs a command in response to detecting that the user moved to perform the command based on prior and current locations of the object.

A method, device and computer program product for controlling the device by tracking a movement of a hand or other objects. The device receives acoustic signals. At least a portion of the received signals are transformed into two-dimensional sinusoids whose frequencies are proportional to an angle-of-arrival (AoA) and a propagation distance of the reflected signals. An AoA-di stance profile is derived based on signals received from the object by evaluating frequencies of the two-dimensional sinusoids. Then, an AoA-di stance pair is derived from the AoA-di stance profile. A current location of the object is determined based on the estimated AoA-di stance pair. The device then performs a command in response to detecting that the user moved to perform the command based on prior and current locations of the object.

Provided is an AI apparatus for determining a location of a user including: a communication unit configured to communicate with at least one external AI apparatus obtaining first image data and first sound data; a memory configured to store location information on the at least one external AI apparatus and the AI apparatus; a camera configured to obtain second image data; a microphone configured to obtain second sound data; and a processor configured to: generate first recognition information on the user based on the second image data; generate second recognition information on the user based on the second sound data; obtain, from the at least one external AI apparatus, third recognition information on the user generated based on the first image data and fourth recognition information on the user generated based on the first sound data; determine the user's location based on the location information, the first recognition information, and the third recognition information; and calibrate the determined user's location based on the second recognition information and the fourth recognition information.

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 method for spatial audio signal processing including: determining at least one first direction parameter for at least one frequency band based on microphone signals received from a first microphone array; determining at least one second direction parameter for the at least one frequency band based on at least one microphone signal received from at least one second microphone, wherein microphones from the first microphone array and the at least one second microphone are spatially separated from each other; processing the determined at least one first direction parameter and the at least one second direction parameter to determine at least one distance parameter for the at least one frequency band; and enabling an output and/or store of the at least one distance parameter, at least one audio signal, and the at least one first direction parameter.

A method for use with a computing device is provided. The method may include executing one or more programs of an intelligent digital assistant system at a processor and presenting a user interface to a user. At the processor, the method may include receiving natural language user input from the user, parsing the user input at an intent handler to determine an intent template with slots, populating the slots in the intent template with information from user input, and performing resolution on the intent template to partially resolve unresolved information. If a slot with missing slot information exists in the partially resolved intent template, a loop may be executed at the processor to fill the slots. The method may include, at the processor, determining that all required information is available and resolved and generating a rule based upon the intent template with all required information being available and resolved.