A method for providing a service based on a user's voice includes steps of extracting a voice of a first user, generating text information or voice waveform information based on the voice of the first user, analyzing a disposition of the first user based on the text information and the voice waveform information, and then selecting a second user corresponding to the disposition of the first user based on the analysis result, providing the first user with a conversation connection service with the second user and acquiring information on a change in an emotional state of the first user based on conversation information between the first user and the second user, and re-selecting the second user corresponding to the disposition of the first user based on the acquired information on the change in the emotional state of the first user.

Based on a detection that a customer has arrived at an enterprise location to pick up a previously-placed order, an intelligent automated customer dialogue system generates an interface via which an intelligent customer dialogue application dialogues with the customer. The application generates and initially offers, at the interface using natural language, content which is contextual to one or more items of the order, e.g., by using a specially trained intelligent dialogue machine learning model. The application may intelligently respond to the customer's natural language responses and/or requests to refine, augment, or redirect subsequently-offered content and/or dialogue, e.g., by using the model. Offered content (e.g., product information, services, coupons, suggestions, recommendations, etc.) generally provides value-add to the customer as well as maintains customer engagement. The system may be implemented at least partially by using a chatbot upon curbside pick-up, for example, as well as through other electronic customer facing channels.

A processor may receive first voice data associated with a first user utterance in conversation in a guided dialog system. The processor may identify from the first voice data a first topic of a set of topics associated with the first user utterance. The processor may identify a first solution associated with the first topic, the first solution having one or more solution segments for accomplishing a task related to the topic. The processor may generate a first response for a second user based on a first solution segment of the first solution and the first voice data.

An electronic apparatus includes: a memory storing a first threshold value and a second threshold value corresponding to a receiving direction of a wake-up word, a sound receiver comprising sound receiving circuitry, and a processor configured to: identify a receiving direction of the sound based on a sound received through the sound receiver, based on a similarity between sound data obtained in response to the received sound and the wake-up word being greater than or equal to the first threshold value corresponding to the identified receiving direction, perform voice recognition for a subsequent sound received through the sound receiver, and based on the similarity being less than the first threshold value and greater than or equal to the second threshold value, change the first threshold value.

A method of controlling a home appliance which operates in an Internet of Things environment through a 5G communication network and which is performed using a neural network model generated by machine learning, including determining whether there is a user in the vicinity of the home appliance, capturing a motion of the user using a vision sensor based on a determination that there is a user in the vicinity of the home appliance, identifying an intention of the user based on the captured motion, and activating a speech module of the home appliance based on the intention of the user.

Disclosed are various aspects of postponing or migrating tasks from a first assistant device to another assistant device. In some examples, an assistant device can facilitate task completion. Tasks can be recommended for postponement based upon the complexity of the task, a historical user profile, or the location of the assistant device.

A method for controlling operation of an appliance by a user through voice control includes at least the steps of: detecting, by the appliance, a control action performed by the user on the appliance; activating a voice control system by the appliance; capturing, by the voice control system, a voice input from the user as a captured voice input; recognizing, by the voice control system, a piece of information and/or an instruction in the captured voice input from the user as a recognized information and/or instruction; and executing, by the voice control system, a user control action on the appliance in accordance with the recognized information and/or instruction.

A response method, a terminal, and a storage medium. The response method comprises: determining, at a first time point by means of speech recognition processing, a first target text corresponding to the first time point (1001); determining, according to the first target text, a first predicted intention and an answer to be pushed, wherein said answer is used for responding to speech information (1002); continuing to determine, by means of the speech recognition processing, a second target text corresponding to a second time point and a second predicted intention, wherein the second time point is the next successive time point of the first time point (1003); determining, according to the first predicted intention and the second predicted intention, whether a preset response condition is satisfied (1004); and responding according to said answer if the preset response condition is determined to be satisfied (1005).

A system for identifying computer agents to perform a particular task requested by a user, receives an audio signal to perform the particular task. The system extracts a set of features from the audio signal. The set of features represents at least a first keyword indicating the particular task. The system determines which one or more computer agents from a plurality of computer agents is predetermined to perform the particular task by comparing the first keyword with a plurality of keywords associated with the plurality of keywords. The system determines a first computer agent associated with a second keyword that corresponds to the first keyword. The system executes the first computer agent to perform the particular task.

Methods and systems for correcting, based on subsequent second speech, an error in an input generated from first speech using automatic speech recognition, without an explicit indication in the second speech that a user intended to correct the input with the second speech, include determining that a time difference between when search results in response to the input were displayed and when the second speech was received is less than a threshold time, and based on the determination, correcting the input based on the second speech. The methods and systems also include determining that a difference in acceleration of a user input device, used to input the first speech and second speech, between when the search results in response to the input were displayed and when the second speech was received is less than a threshold acceleration, and based on the determination, correcting the input based on the second speech.