Implementations set forth herein allow a user to access a first application in a foreground of a graphical interface, and simultaneously employ an automated assistant to respond to notifications arising from a second application. The user can provide an input, such as a spoken utterance, while viewing the first application in the foreground in order to respond to notifications from the second application without performing certain intervening steps that can arise under certain circumstances. Such intervening steps can include providing a user confirmation, which can be bypassed, and/or time-limited according to a timer, which can be displayed in response to the user providing a responsive input directed at the notification. A period for the timer can be set according to one or more characteristics that are associated with the notification, the user, and/or any other information that can be associated with the user receiving the notification.

The speech processing apparatus 100 includes an air microphone speech recognition unit 101 which recognizes speech from an air microphone 200 acquiring speech through air, a wearable microphone speech recognition unit 102 which recognizes speech from a wearable microphone 300, a sensing unit 103 which measures environmental conditions, a weight decision unit 104 which calculates the weights for recognition results of the air microphone speech recognition unit 101 and the wearable microphone speech recognition unit 102 on the basis of the environmental conditions, and a combination unit 105 which combines the recognition results outputted from the air microphone speech recognition unit 101 and the wearable microphone speech recognition unit 102, using the weights.

A method, computer system, and a computer program product for managing a plurality of electronic devices controlling access to one or more hazards in a physical environment. The present invention may include detecting a plurality of brain-wave patterns associated with a user. The present invention may then, in response to detecting motion of the user and the plurality of brain-wave patterns associated with the user matching a pattern, include operating at least one electronic device to disable access to a corresponding hazard. The present invention may further include operating the at least one electronic device to enable access to the corresponding hazard based on receiving input from the user to enable the at least one electronic device, wherein the input being received from the user is in response to prompting the user to correctly respond to a question previously answered by the user.

In one embodiment, a method includes receiving a user request including an ambiguous mention to create a reminder from a client system associated with a user, disambiguating the mention to identify a first entity referenced in the mention, wherein the first entity is identified based on user profile data associated with the user, determining an activation condition associated with the user request, wherein the activation condition is based on one or more of a time or a location referenced in the user request, wherein the time and/or location are determined based on contextual information associated with the user request, generating the reminder based on the first entity and the activation condition, and sending instructions to the client system for presenting the reminder when the activation condition is satisfied.

Devices and techniques are generally described for generating and evaluating utterances. In some examples, an utterance generation and evaluation system can receive intent data and target data. The utterance generation and evaluation system can determine related target names and related intent names and, based on the related target names and related intent names, can generate an utterance phrase. The utterance generation and evaluation system can determine a confidence score associated with the utterance phrase and, based on the confidence score, determine the utterance phrase as a recommended utterance phrase.

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.

An electronic apparatus is provided. The electronic apparatus includes a memory and a processor configured to control the electronic apparatus to: classify a plurality of input data into a plurality of types to store in the memory, determine at least one among the input data of the classified plurality of types based on a voice command being recognized among the input data, and provide response information corresponding to the voice command based on the input data of the determined type.

Systems and methods for establishing user persona from audio interactions are disclosed, including a voice-based conversational AI platform having an acoustic analytical record engine and audio signal codification optimizer. The engine receives an audio sample indicative of voice conversation between an end user and a bot and transforms it into quantifiable and machine-ingestible power spectrum and acoustic indicators that uniquely represent the audio sample in the form of a feature vector. The optimizer ingests and processes the indicators to estimate likelihood of an attribute value representing the audio sample by constructing a convolutional neural network model for each attribute category. The optimizer establishes user persona attribute values across different attribute categories for the audio sample based on the estimated likelihood. Finally, a Textual Latent Value Extractor of the system determines the issue's context window and estimates the statements polarity to provide distinguishable insight in business strategy and development.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, relating to synthetic call status updates. In some implementations, a method includes determining, by a task manager module, that a triggering event has occurred to provide a current status of a user call request. The method may then determine, by the task manager module, the current status of the user call request. A representation of the current status of the user call request is generated. Then, the generated representation of the current status of the user call request is provided to the user.