Abstract: An electronic apparatus includes a communication interface configured to communicate with an external device; a speaker; a memory storing at least one instruction; and at least one processor operatively connected to the communication interface, the speaker, and the memory, wherein the at least one processor is configured to execute the at least one instruction to: based on a voice signal being received from an external device through the communication interface, identify whether the external device is a privacy device; based on identifying that the external device is a privacy device, output a response signal regarding the voice signal to the external device through the communication interface; and based on identifying that the external device is not a privacy device, output a response signal regarding the voice signal through the speaker.

Abstract: Implementations are directed to generating voice-based chatbot policy override(s) and/or utilizing voice-based chatbot policy override(s) in conjunction with existing voice-based chatbot(s). The voice-based chatbot policy override(s) can correspond to, for example, machine learning (ML) model(s) that supplement functionality of the existing voice-based chatbot(s). Notably, the voice-based chatbot policy override(s) are associated with rule(s) (e.g., by virtue of training the ML model(s) that correspond to the voice-based chatbot policy override(s)) for when the voice-based chatbot policy override(s) should be utilized in lieu of the existing voice-based chatbot(s) in responding to spoken utterance(s) of human user(s) engaged in corresponding conversation(s) with the voice-based chatbot policy override(s). Nonetheless, from a perspective of the human user(s), it appears as if they are still engaging in the corresponding conversations with the existing voice-based chatbot(s).

Abstract: In one aspect, a playback device includes a voice assistant service (VAS) wake-word engine and a command keyword engine. The playback device detects, via the command keyword engine, a first command keyword, and determines whether one or more playback conditions corresponding to the first command keyword are satisfied. Based on (a) detecting the first command keyword and (b) determining that the one or more playback conditions corresponding to the first command keyword are satisfied, the playback device playback device performs a first playback command corresponding to the first command keyword. When the playback device detects, via the wake-word engine, a wake-word in voice input, the playback device streams sound data corresponding to at least a portion of the voice input to one or more remote servers associated with the VAS.

Abstract: A sound collection apparatus A server (10) causes a terminal device (30) to display a setting user interface, and receives a prohibition time zone setting command. Server sets a prohibition time zone for a target device based on the prohibition time zone setting command. Server (10) causes the target device to utter, when a time for causing the target device to utter is determined not to correspond to the prohibition time zone.

Abstract: In some embodiments, the present invention provides for an exemplary computer system which includes at least the following components: an adaptive self-trained computer engine programmed, during a training stage, to electronically receive an initial speech audio data generated by a microphone of a computing device; dynamically segment the initial speech audio data and the corresponding initial text into a plurality of user phonemes; dynamically associate a plurality of first timestamps with the plurality of user-specific subject-specific phonemes; and, during a transcription stage, electronically receive to-be-transcribed speech audio data of at least one user; dynamically split the to-be transcribed speech audio data into a plurality of to-be-transcribed speech audio segments; dynamically assigning each timestamped to-be-transcribed speech audio segment to a particular core of the multi-core processor; and dynamically transcribing, in parallel, the plurality of timestamped to-be-transcribed speech audio segm

Abstract: Systems and methods to provide action recommendations based on audio information are disclosed.

Abstract: Dialog acts (e.g., questions) are selected for voice browsing by a model trained to identify a dialog act that is most likely to lead to a desired outcome. Upon receiving an invocation to begin a conversation, a score indicative of a level of confidence that the conversation will have a successful outcome is determined, and a dialog act is selected based on the score. Subsequently, at each turn of the conversation, the score is updated or a new score is calculated, and a dialog act is selected based on the updated or new score. Confidence scores are calculated based on input features that are determined based on the user who uttered the invocation or responses to dialog acts, as well as a context of the conversation, and provided to a linear model or a machine learning model as inputs.

Abstract: In one embodiment, a method includes receiving a voice input from a first user from a client system via an assistant xbot associated with an assistant system, determining that the voice input includes an out-of-coverage request including intents or slots that are unsupported by the assistant system, generating a contextual response for the out-of-coverage request, wherein the contextual response includes an implicit confirmation of the out-of-coverage request and a failure response to the out-of-coverage request, wherein the implicit confirmation references the voice input from the first user, and wherein the failure response indicates that the assistant system is unable to execute a task corresponding to the out-of-coverage request, and sending instructions for presenting the contextual response responsive to the voice input to the client system.

Abstract: Disclosed in the embodiments of the present disclosure are an audio playback method and apparatus, a computer readable storage medium, and an electronic device. The method includes: acquiring intention determination data collected for at least one user within a target space; determining that at least one user has a target vocal intention based on the intention determination data, and then determining feature information representing a current feature of the at least one user; and extracting and playing an audio corresponding to the feature information from a preset audio library. According to the embodiments of the present disclosure, it is achieved to automatically perform a determination on the target vocal intention of the user by the electronic device, without triggering an audio playing operation by the user, the steps of performing the audio playing operation by the user being omitted, and the convenience of the audio playing operation being improved.

Abstract: Techniques related to a method and system of audio false keyphrase rejection using speaker recognition are described herein. Such techniques use speaker recognition of a computer originated voice to omit actions triggered when a keyphrase is present in captured audio and omitted when speech of the captured audio was spoken by the computer originated voice.

Abstract: Disclosed are a display apparatus, and display method. The display apparatus includes a display, a control device configured to control the display apparatus and including a power key and a shortcut key for voice control, a voice receiving device configured for receiving voice content from a user and a controller, in connection with the display, the control device and the voice receiving device.

Abstract: A platform implements tensor-based reinforcement learning for communication channel optimization. Using an audio data feed, the platform generates a set of alphanumeric input features associated with an entity interaction. Using the features, a neural network generates a first node parameter set for a first node of a channel optimization map. The platform instantiates a communication session with a computing device via a communication channel indicated by communication channel parameter(s) in the first node parameter set. Using a timing parameter, a tone parameter, a content parameter, and/or a nudge parameter, an electronic message can be generated for transmission via the communication channel. Using the neural network, the platform processes feedback data received via the channel to generate a second node for the channel optimization map. Configuration of the neural network can be updated, using the feedback data, by applying reinforcement learning or another suitable technique.

Abstract: An example electronic device includes communication circuitry, a processor, and a memory that stores instructions. The electronic device may be configured to obtain utterance data and location information of a user, identify a type and control function of a target device based on the utterance data, identify a plurality of candidate electronic devices corresponding to the location information and the type, identify a common function between the plurality of candidate electronic devices based on identification of the plurality of candidate electronic devices, provide a notification by differently controlling the common function for each of the plurality of candidate electronic devices, obtain, from the user, response utterance data including a response to the notification, determine the target device that is to perform the control function among the plurality of candidate electronic devices based on the response utterance data, and control the target device to perform the control function.

Abstract: [Problem] Provided is a conversation assistance method using a computer that ensures evaluating a conversation in real time. [Solution] A conversation assistance method using a computer includes a voice analysis step, a word group analysis step, and a remark evaluation step executed by the computer. The voice analysis step is for analyzing a voice related to a conversation and obtaining a voice word that is a word included in the conversation. The word group analysis step is for analyzing which among a plurality of term groups including either one of or both of a word and a phrase the voice word corresponds to. The remark evaluation step evaluates a remark every time a remark related to the conversation is input, based on the term group analyzed in the word group analysis step.

Abstract: Provided is a system that performs proper display under recognition of vocalizer in conversation. An explanation support system 1 includes a display unit 3, a material storage unit 5 that stores an explanation material and a plurality of keywords related to the explanation material, a display information storage unit 7 that stores display information displayed on the display unit 3 based on a combination of the keywords, a voice analysis unit 9 that analyzes voice terms that are terms included in voice information related to the explanation material and vocalizers of the voice terms, and a display control unit 11 that identifies which of the plurality of keywords the voice term of a specific vocalizer analyzed by the voice analysis unit 9 is, reads out the display information from the display information storage unit 7 using information related to the identified keyword, and causes the display unit 3 to display the display information.

Abstract: Systems and methods are disclosed for generating internal state representations of a neural network during processing and using the internal state representations for classification or search. In some embodiments, the internal state representations are generated from the output activation functions of a subset of nodes of the neural network. The internal state representations may be used for classification by training a classification model using internal state representations and corresponding classifications. The internal state representations may be used for search, by producing a search feature from an search input and comparing the search feature with one or more feature representations to find the feature representation with the highest degree of similarity.

Abstract: Implementations set forth herein (elate to an automated assistant capable of bypassing soliciting a user for supplemental data for completing an action when a previously-queried application is capable of providing the supplemental data. For instance, when a user invokes the automated assistant to complete a first action with a first application, the user may provide many pertinent details. Those details may be useful to a second application that the user may subsequently invoke via the automated assistant for completing a second action. In order to save the user from having to repeat the details to the automated assistant, the automated assistant can interact with the first application in order to obtain any information that may be essential for the second application to complete the second action. The automated assistant can then provide the information to the second application, without soliciting the user for the information.

Abstract: In order to assist a voice recognition function when voice recognition has failed, a display device may comprise a display, a user input interface configured to receive a command from a remote control device, and a controller configured to display a keyboard window including one or more queries and a keyboard item on the display when voice recognition for a voice command uttered by a user has failed in a state in which a voice recognition function is activated.

Abstract: A computer-implemented method of controlling an output from a dialogue system, the method comprising: receiving, by way of an input, first input data relating to speech or text provided by a user; selecting a first state from a plurality of states of a deterministic model, at least some states of the plurality of states being associated with a corresponding portion of a language model prompt including an instruction to call a corresponding function; responsive to the first state being associated with a corresponding portion, generating a first language model prompt comprising at least part of the corresponding portion associated with the selected first state; providing the first language model prompt as input to a language model to generate a first language model output; determining whether to execute a function based on the first language model output; responsive to determining to execute a first function based on the first language model output, executing the determined first function to generate a first

Abstract: A computing device parses a user-specified natural language command to form a first expression. The computing device determines that the first expression is ambiguous or underspecified. The computing device, in accordance with the determination, infers first information using one or more inferencing rules, where at least one of the inferencing rules is based on an attribute of data fields and/or data values in a data source. The computing device forms a second expression based on the first expression using and the first information. The computing device retrieves one or more data sets from the data source using according to the second expression. The computing device generates and displays a data visualization of the retrieved one or more data sets.