A smoking cessation system of a vehicle includes: a microphone configured to generate an output based on sound within a passenger cabin of the vehicle; a virtual assistant module configured to identify a future smoking event within the passenger cabin of the vehicle based on the output of the microphone; and a smoking module configured to take at least one remedial action in response to the identification of a future smoking event.

A vehicle includes a plurality of microphones to obtain speech from a person outside the vehicle as an input signal and a sensor system to determine a location and orientation of the person relative to the vehicle. The vehicle also includes a controller to determine characteristics of the input signal and to determine whether to perform speech enhancement on the input signal based on one or more of the characteristics and the location and orientation of the person.

Described herein is a system for responding to a frustrated user with a response determined based on spoken language understanding (SLU) processing of a user input. The system detects user frustration and responds to a repeated user input by confirming an action to be performed or presenting an alternative action, instead of performing the action responsive to the user input. The system also detects poor audio quality of the captured user input, and responds by requesting the user to repeat the user input. The system processes sentiment data and signal quality data to respond to user inputs.

A dialog assistance apparatus facilitates a dialog by including a first estimation unit that estimates, with respect to a field related to speech content of a first speaker, a knowledge level of a second speaker having a dialog with the first speaker, an acquisition unit that acquires, from a storage unit that stores a question in association with a keyword and the knowledge level, a question corresponding to a keyword included in the speech content and corresponding to the knowledge level of the second speaker, and an output unit that outputs the acquired question to the first speaker.

In one embodiment, a method includes receiving a user request from a first user at a client system, wherein the user request is associated with a semantic-intent, identifying dialog-intents associated with the user request by the client system based on the semantic-intent and context information associated with the user request, wherein each dialog-intent is a sub-intent of the semantic-intent; determining agents for executing tasks associated with the dialog-intents by the client system, and presenting information returned from the agents responsive to executing the tasks at the client system.

Systems and methods are provided for providing an augmented reality experience. The systems and methods perform operations comprising: generating, for display by a messaging application, an image comprising one or more augmented reality elements, the one or more augmented reality elements being associated with a configurable entity; receiving, by the messaging application, speech input from a user; determining a schema associated with the one or more augmented reality elements; causing the speech input to be processed by a speech understanding model in accordance with the schema to determine one or more configurable state entity update values; updating the configurable entity associated with the one or more augmented reality elements based on the one or more configurable state entity update values; and modifying the one or more augmented reality elements in the image based on the updated configurable entity.

Implementations relate to determination and visual display of spoken menus for calls. In some implementations, a computer-implemented method includes receiving audio data output in a call between a call device and a device associated with a target entity. The audio data includes speech indicating one or more selection options for a user of the call device to navigate through a call menu provided by the target entity in the call. Text is determined by programmatically analyzing the audio data, the text representing the speech. The selection options are determined based on programmatically analyzing at least one of the text or the audio data. At least a portion of the text is displayed by the call device during the call, as one or more visual options that correspond to the selection options. The visual options are each selectable via user input to cause corresponding navigation through the call menu.

A brainwave feedback system, adapted to generate feedback based on a user's brainwave, the brainwave feedback system comprises: a brainwave sensing device, configured to obtain a first brainwave signal of the user; a server, storing a keyword string pool including a plurality of sorted keywords, and performing a feedback procedure when a first physiological parameter falls outside of a predetermined parameter range, wherein the first physiological parameter is associated with the first brainwave signal, the feedback procedure includes choosing a keyword from the keyword string pool by the server as a feedback keyword, and outputting the feedback keyword; and an output component, in communicable connection with the server, wherein the output component presents an analysis result corresponding to the first physiological parameter. The present disclosure further discloses an operation method of brainwave feedback system.

Integrating behavioral and lexical analysis of conversational audio signals with CRM (Customer Relationship Management) workflow analysis signals to provide real-time guidance to agents who are both speaking with a customer telephonically and interacting with the customer's information using a CRM system. This includes intaking audio and CRM analysis signals in real-time, extracting the behavioral and lexical signals from the audio. The CRM, behavioral, and lexical information are combined to produce guidance and scoring signals, which are output to the CRM in real-time to facilitate real-time guidance and scoring. The data can be stored for future reference.

A method is for automatic interaction with a patient during a magnetic resonance examination with a magnetic resonance apparatus. In an embodiment, the method includes detecting an acoustic utterance of the patient; processing the acoustic utterance of the patient via a speech processor, the processing of the acoustic utterance including at least determining the communication as a function of the acoustic utterance and checking the communication for a correlation with a parameter of the magnetic resonance examination; determining the output as a function of the communication of the patient and the parameter of the magnetic resonance examination and providing the output. A magnetic resonance apparatus of an embodiment includes at least a processor to carry out an embodiment of the method. The method can further be stored on a computer program product or medium for execution by a processor.