Abstract: A masking device for a virtual assistant, the masking device including a body configured to at least partially block a virtual assistant microphone of the virtual assistant, and an assistant initializer in or on an inside of the body. The masking device also includes a masking device microphone on an outside of the body, and a processor communicatively connected to the assistant initializer and the microphone. The processor is configured to employ the assistant initializer to control an audio communication channel to the virtual assistant in response to the microphone receiving a first audio key term from a user.

Abstract: 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.

Abstract: Smart speaker system mechanisms, associated with a smart speaker device comprising an audio capture device, are provided for processing audio sample data captured by the audio capture device. The mechanisms receive, from the audio capture device of the smart speaker device, an audio sample captured from a monitored environment. The mechanisms classify a sound in the audio sample data as a type of sound based on performing a joint analysis of a plurality of different characteristics of the sound and matching results of the joint analysis to criteria specified in a plurality of sound models. The mechanisms determine, based on the classification of the sound, whether a responsive action is to be performed based on the classification of the sound. In response to determining that a responsive action is to be performed, the mechanisms initiate performance of the responsive action by the smart speaker system.

Abstract: A facility for representing a mandate occurring in an authority document with a control is described. For each of one or more controls in a set of existing controls, the facility determines a similarity score measuring the similarity of the mandate and the control; where the similarity score exceeds a similarity threshold, the facility links the mandate to the control. Where the mandate is not linked to any control in the set of controls, the facility adds a control to the set of controls that is based on the mandate, and links the mandate to the added control.

Abstract: A user engages in spoken voice or messaging platform-based natural language dialogues with an automated bot. The bot identifies actions and subjects of the actions from the dialogues and processes Application Programming Interfaces (API) to perform travel-related queries or process travel-related transactions with travel services. Real-time responses to queries or completed transaction notifications are provided back to the user by the bot during the dialogues.

Abstract: In some implementations, a determination that a first party has spoken a query for a voice-enabled virtual assistant during a voice call between the first party and a second party is made, in response to the determination that the first party has spoken the query for the voice-enabled virtual assistant during the voice call between the first party and the second party, the voice call between the first party and the second party is placed on hold, a determination that the voice-enabled virtual assistant has resolved the query is made, and in response to the determination that the voice-enabled virtual assistant has handled the query, the voice call between the first party and the second party is resumed from hold.

Abstract: Web content with a speech interaction user interface capability is provided. Interactable elements of the web content are identified. For each of the interactable elements, one or more associated identifiers are determined and associated with a corresponding interactable element of the identified interactable elements in a data structure. A speech input is received from a user. Using the data structure, one of the interactable elements is matched to the received speech input. An action is automatically performed on the matched interactable element.

Abstract: In one embodiment, a domain-name based framework implemented in a digital assistant ecosystem uses domain names as unique identifiers for request types, requesting entities, responders, and target entities embedded in a natural language request. Further, the framework enables interpreting natural language requests according to domain ontologies associated with different responders. A domain ontology operates as a keyword dictionary for a given responder and defines the keywords and corresponding allowable values to be used for request types and request parameters. The domain-name based framework thus enables the digital assistant to interact with any responder that supports a domain ontology to generate precise and complete responses to natural language based requests.

Abstract: A method for more efficient structural parsing of binary representations of text based objects within a data distribution system. Clients subscribe to a topic maintained by the data distribution system server that publishers can publish to. Clients receive an original binary representation of a text based object describing the state of the topic to which the client is subscribed. In response to the state of the topic changing at the data distribution system server, clients receive a binary delta representing the change of the state of the topic. Based on the received binary representation and the binary delta, clients calculate an updated binary representation of the text based object. Using the original binary representation, the updated binary representation, and the binary delta, the client generates a structural delta representing the structural differences between data structures of the original text based object and data structures of the updated text based object.

Abstract: In some implementations, a determination that a first party has spoken a query for a voice-enabled virtual assistant during a voice call between the first party and a second party is made, in response to the determination that the first party has spoken the query for the voice-enabled virtual assistant during the voice call between the first party and the second party, the voice call between the first party and the second party is placed on hold, a determination that the voice-enabled virtual assistant has resolved the query is made, and in response to the determination that the voice-enabled virtual assistant has handled the query, the voice call between the first party and the second party is resumed from hold.

Abstract: Disclosed are an electronic device capable of efficiently performing speech recognition and natural language understanding and a method for controlling thereof. The electronic device includes: a microphone; a non-volatile memory configured to store virtual assistant model data comprising data that is classified according to a plurality of domains and data that is commonly used for the plurality of domains; a volatile memory; and a processor configured to: based on receiving, through the microphone, a trigger input to perform speech recognition for a user speech, initiate loading the virtual assistant model data from the non-volatile memory into the volatile memory, load, into the volatile memory, first data from among the data classified according to the plurality of domains and, while loading the first data into the volatile memory, load at least a part of the data commonly used for the plurality of domains into the volatile memory.

Abstract: Techniques are described herein for enabling an automated assistant to adjust its behavior depending on a detected vocabulary level or other vocal characteristics of an input utterance provided to an automated assistant. The estimated vocabulary level or other vocal characteristics may be used to influence various aspects of a data processing pipeline employed by the automated assistant. In some implementations, one or more tolerance thresholds associated with, for example, grammatical tolerances or vocabulary tolerances, may be adjusted based on the estimated vocabulary level or vocal characteristics of the input utterance.

Abstract: A refrigerator comprises a storage compartment configured to store food, a temperature detector configured to detect an internal temperature of the storage compartment, a cooler configured to supply cool air to the storage compartment, a microphone configured to receive a speech, a display configured to display information, at least one processor configured to be electrically connected to the temperature detector, the microphone, and the display; and a memory configured to be electrically connected to the at least one processor.

Abstract: An embodiment for speech-to-text auto-scaling of computational resources is provided. The embodiment may include computing a delta for each word in a transcript between a wall clock time and a time when the word is delivered to a client. The embodiment may also include submitting the deltas to a group of metrics servers. The embodiment may further include requesting from the group of metrics servers current values of the deltas. The embodiment may also include determining whether the current values of the deltas exceed a pre-defined max-latency threshold. The embodiment may further include adjusting the allocated computational resources based on a frequency of the current values of the deltas that exceed the pre-defined max-latency threshold. The embodiment may also include creating a histogram from the current values of the deltas and scaling-up the allocated computational resources based on a percentage of data points that fall above the pre-defined max-latency threshold.

Abstract: Disclosed are a speech recognition method and a speech recognition device, in which speech recognition is performed by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm provided therein. According to an embodiment of the present disclosure, the speech recognition method includes buffering an inputted spoken utterance, determining whether a preset wake-up word is present in the spoken utterance by comparing the buffered spoken utterance to the preset wake-up word, and in response to the preset wake-up word in the spoken utterance, activating a speech recognition function and isolating, from the spoken utterance, a spoken sentence as a voice command without the wake-up word, and processing the spoken sentence and outputting a processing result.

Abstract: The present disclosure provides a method and an apparatus for waking up via a speech. The method includes: obtaining audio data currently collected by an electronic device through an audio-video interface on a hardware abstraction layer of the electronic device; performing noise reduction processing on the collected audio data to generate audio data to be detected; performing wake-up phrase detection on the audio data to be detected to determine whether the audio data to be detected includes a wake-up phrase; and performing wake-up processing on the electronic device in response to determining that the audio data to be detected comprises the wake-up phrase.

Abstract: Techniques are described herein for enabling an automated assistant to adjust its behavior depending on a detected age range and/or “vocabulary level” of a user who is engaging with the automated assistant. In various implementations, data indicative of a user's utterance may be used to estimate one or more of the user's age range and/or vocabulary level. The estimated age range/vocabulary level may be used to influence various aspects of a data processing pipeline employed by an automated assistant. In various implementations, aspects of the data processing pipeline that may be influenced by the user's age range/vocabulary level may include one or more of automated assistant invocation, speech-to-text (“STT”) processing, intent matching, intent resolution (or fulfillment), natural language generation, and/or text-to-speech (“TTS”) processing. In some implementations, one or more tolerance thresholds associated with one or more of these aspects, such as grammatical tolerances, vocabularic tolerances, etc.

Abstract: Systems and methods are provided herein for responding to a voice command at a volume level based on a volume level of the voice command. For example, a media guidance application may detect, through a first voice-operated user device of a plurality of voice-operated user devices, a voice command spoken by a user. The media guidance application may determine a first volume level of the voice command. Based on the volume level of the voice command, the media guidance application may determine that a second voice-operated user device of the plurality of voice-operated user devices is closer to the user than any of the other voice-operated user devices. The media guidance application may generate an audible response, through the second voice-operated user device, at a second volume level that is set based on the first volume level of the voice command.

Abstract: Systems and methods for determining whether a first electronic device detects a media item that is to be output by a second electronic device is described herein. In some embodiments, an individual may request, using a first electronic device, that a media item be played on a second electronic device. The backend system may send first audio data representing a first response to the first electronic device, along with instructions to delay outputting the first response, as well as to continue sending audio data of additional audio captured thereby. The backend system may also send second audio data representing a second response to the second electronic device along with the media item. Text data may be generated representing the captured audio, which may then be compared with text data representing the second response to determine whether or not they match.

Abstract: Methods and apparatus to identify sources of network streaming services using windowed sliding transforms are disclosed.