Abstract: Provided are a display apparatus, a control method thereof, a server, and a control method thereof. The display apparatus includes: a processor which processes a signal; a display which displays an image based on the processed signal; a first command receiver which receives a voice command; a storage which stores a plurality of voice commands said by a user; a second command receiver which receives a user's manipulation command; and a controller which, upon receiving the voice command, displays a list of the stored plurality of voice commands, selects one of the plurality of voice commands of the list according to the received user's manipulation command and controls the processor to process based on the selected voice command.

Abstract: Embodiments provide a social networking platform offering various services, such as, facilitating aggregation and management of a user's interaction on one or more social networking platforms, offering enhanced control over the level of privacy associated with the flow of user data, offering tools to customize the user's exposure to advertisement-related content on the social networking platform(s), integrating features to control aspects of how data/content is presented to and visualized by the user, empowering the user to multicast direct messages to other users without the other users having to meet certain constraints, empowering the user to create and/or join a group based on messaging threads, and the like. One or more of these enhanced services/features are associated with a powerful framework of authentication/permission model for access control.

Abstract: A text recognition method and apparatus, and a storage medium are provided. The method includes: obtaining sample text data, the sample text data comprising a plurality of sample phrases; and generating a recognition model based on the sample phrases by performing training on a plurality of training nodes. Generating the recognition model includes respectively obtaining, by each of the plurality of training nodes, recognition coefficients of the sample phrases distributed to the corresponding training node; and determining, by the plurality of training nodes, model parameters of the recognition model according to the recognition coefficients of the sample phrases. The method also includes obtaining to-be-recognized text data; inputting the text data to the recognition model; and obtaining recognized target text data output by the recognition model and corresponding to the text data.

Abstract: An emergency event detection and response system detects an occurrence of an event associated with a user and initiates an emergency response flow. A user may be associated with a wearable device and have in his home a base station and portable or stationary wireless devices containing sensors capable of detecting an emergency event. The emergency event may be detected based on voice or non-voice audio input from the user, data monitoring by the wearable device, base station, and/or portable or stationary wireless device, or by physical button press. Responsive to determining that an emergency event has occurred, the system triggers an emergency response flow by notifying a call center and contacting one or more caregivers associated with the user. Caregivers may access a response system application to receive updates regarding the detected emergency and to contact the user and/or a provider associated with the call center.

Abstract: A listening device that identifies, based on receiving the digitized voice stream, a first keyword of a plurality of keywords in the digitized voice stream. For example, the keyword may be a name associated with a service provider (e.g., “Google”). In response to identifying the first keyword of the plurality of keywords in the digitized voice stream the listening device identifies a first communication address of a first communication server of a first service provider associated with the first keyword of the plurality of keywords in the digitized voice stream. The listening server then routes the digitized voice stream and/or information associated with the digitized voice stream to the first communication server of the first service provider using the first communication address.

Abstract: A conversation guidance method of a speech recognition system may include managing a user domain based on speech recognition function information and situation information corrected from a system mounted on a vehicle, generating a conversation used for speech recognition based on the user domain, and guiding a user with the generated conversation.

Abstract: There is provided a system and method for processing and/or recognizing acoustic signals. The method comprises obtaining at least one pre-existing speech recognition model; adapting and/or training the at least one pre-existing speech recognition model incrementally when new, previously unseen, user-specific data is received, the data comprising input acoustic signals and/or user action demonstrations and/or semantic information about a meaning of the acoustic signals, wherein the at least one model is incrementally updated by associating new input acoustic signals with input semantic frames to enable recognition of changed input acoustic signals. The method further comprises adapting to a user's vocabulary over time by learning new words and/or removing words no longer being used by the user, generating a semantic frame from an input acoustic signal according to the at least one model, and mapping the semantic frame to a predetermined action.

Abstract: A system for providing help includes a preprogrammed kit that includes at least one digital assistant and a virtual private network repeater for connecting to a data provider for connecting the digital assistant to a server. A plurality of agent computers is connected to the server by a data network. The digital assistant is preprogrammed with a skill for recognizing a preprogrammed specific utterance and the digital assistant is pre-configured to connect with the virtual private network repeater. After the preprogrammed specific utterance is detected by the digital assistant, the digital assistant initiates a request for help to the server and upon receiving the request for the help, the server assigns one of the agent computers and forwards the request for help to the one of the agent computers.

Abstract: Method starts with processing, by a processor, audio signal to generate audio caller utterance and transcribed caller utterance. Processor generates identified task based on transcribed caller utterance. Processor samples audio caller utterance to generate samples of audio caller utterance. Processor generates loudness result based on loudness values of samples using loudness neural network associated with identified task. Processor generates pitch result based on pitch values of samples using pitch neural network associated with identified task. Processor generates tone result for each word in transcribed caller utterance using tone neural network associated with identified task. Using task completion probability neural network associated with identified task, processor generates task completion probability result that is based on at least one of: loudness result, pitch result, or tone result. Other embodiments are disclosed herein.

Abstract: An artificial intelligence (AI) system configured to simulate functions of a human brain, such as recognition, determination, etc., by using a machine learning algorithm, such as deep learning, etc., and an application thereof. The AI system includes a method performed by a device to transmit and receive audio data to and from another device includes obtaining a voice input that is input by a first user of the device, obtaining recognition information indicating a meaning of the obtained voice input, transmitting the obtained voice input to the other device, determining whether an abnormal situation occurs, in which a second user of the other device does not understand the transmitted voice input, and transmitting the obtained recognition information to the other device, based on a result of the determination.

Abstract: The present invention provides a speech processing method, which includes: receiving speech information; recognizing the speech information to convert the speech information into a plurality of pieces of text information; displaying at least one pieces of the text information; and receiving a selection signal to respond according to selected text information. The present invention further provides a speech processing device. According to the speech processing method and device provided by embodiments of the present invention, a user can select and confirm by clicking on displayed text information after the speech information is recognized, so that the selected text information is guaranteed to be coincident with a received speech information, thus further increasing accuracy and convenience of the speech processing and providing the user with a good experience effect.

Abstract: Method and system are provided for compensating for user hand tremors when using a hand-held electronic device having a user interface display. The method includes monitoring position data of a user's finger in relation to the user interface display over time as the finger approaches an element in the user interface display. A target element is determined by predicting an intended movement of the user's finger and the method dynamically enlarges the determined target element in the user interface display as the user's finger approaches the user interface display.

Abstract: A method, performed by a dialogue processing device, of processing dialogue associated with a user based on dialog act information, the method comprises receiving speech information, corresponding to speech of the user, including a plurality of sentence units; identifying a first sentence unit and a second sentence unit, of the plurality of sentence units, based on receiving the speech information; extracting a first dialog act indicative of an intention of the first sentence unit and extracting a second dialog act indicative of an intention of the second sentence unit; extracting a first dialog act indicative of an intention of the first sentence unit and extracting a second dialog act indicative of an intention of the second sentence unit; processing the first sentence unit and the second unit in a sequence according to respective priority orders assigned based on a number of empty slots of dialogue frames of the sentence units.

Abstract: The present disclosure provides systems and methods for selecting and presenting content items based on user input. The method includes receiving first input intended to identify a desired content item among content items associated with metadata, determining that an input portion has an importance measure exceeding a threshold, and providing feedback identifying the input portion. The method further includes receiving second input, and inferring user intent to alter or supplement the first input with the second input. The method further includes, upon inferring intent to alter the first input, determining an alternative query by modifying the first input based on the second input, and, upon inferring intent to supplement the first input, determining an alternative query by combining the first input and the second input. The method further includes selecting and presenting a subset of content items based on comparing the alternative query and metadata associated with the subset.

Abstract: An electronic device includes a housing, a touch screen display exposed through a first area of the housing, a microphone exposed through a second area of the housing, a wireless communication circuit, a processor electrically connected to the touch screen display, the microphone, and the wireless communication circuit, and a memory electrically connected to the processor and storing instructions.

Abstract: Embodiments disclosed herein are related to computing systems, and methods for determining patterns in received data that are indicative of common characteristics of the one or more users of a computing system. Data from first users of the computing system is received. The received data defines information about the first users. The type of the data that is received is determined by the first users. The received data is analyzed to determine one or more patterns in the received data. The one or more patterns are indicative of one or more common characteristics shared by the first users. Information related to the determined one or more patterns is provided to second users. The information includes a DID for each of the f first users that may be used by the second users to communicate with the first users.

Abstract: A method is provided in accordance with an aspect of the present disclosure. The method includes detecting at least one voice input from a user of an electronic device, transforming the at least one voice input into a text structure including at least one word, and determining a current context scope of the electronic device. The method also includes comparing the text structure to a plurality of existing text structures, where each of the existing text structure associated with a command for an action on the electronic device. The method further includes identifying, when the text structure matches with at least one of the existing text structures, a command to correspond to the at least one voice input from the user, and performing an action on the electronic device based on the identified command.

Abstract: A conversation for simulation by an artificial intelligence-based tutor is automatically generated. The conversation relates to content on which the artificial intelligence-based tutor is being trained. The automatically generating the conversation includes automatically generating inputs from a simulated student regarding the content, and automatically generating on behalf of the artificial intelligence-based tutor expected responses to the inputs generated from the simulated student. The conversation is provided as an output to be input to the artificial intelligence-based tutor for simulation by the artificial intelligence-based tutor.

Abstract: A speech processing apparatus is provided in which, while face feature points are extracted from moving image data obtained by imaging a speaker's face, for each frame, a first generation network for generating face feature points of the corresponding frame based on speech feature data extracted from uttered speech of the speaker for each frame is generated, and whether the first generation network is appropriate is evaluated using an identification network, then, a second generation network for generating the uttered speech from a plurality of uncertain settings including at least text representing utterance content of the uttered speech and information indicating emotions included in the uttered speech, a plurality of types of fixed settings which define speech quality, and the face feature points generated by the first generation network evaluated as appropriate, is generated, and whether the second generation network is appropriate is evaluated using the identification network.

Abstract: A computing system can determine a vehicle command based on a received spoken language command and determined confidence levels. The computing system can operate a vehicle based on the vehicle command. The computing system can further determine the spoken language command by processing audio spectrum data corresponding to spoken natural language with an automatic speech recognition (ASR) system.

Abstract: This relates to systems and processes for using a virtual assistant to arbitrate among and/or control electronic devices. In one example process, a first electronic device samples an audio input using a microphone. The first electronic device broadcasts a first set of one or more values based on the sampled audio input. Furthermore, the first electronic device receives a second set of one or more values, which are based on the audio input, from a second electronic device. Based on the first set of one or more values and the second set of one or more values, the first electronic device determines whether to respond to the audio input or forego responding to the audio input.

Abstract: A computer speech output control method, system, and non-transitory computer readable medium, include a computer speech output unit configured to output a computer speech, a human speech monitoring circuit configured to determine whether ambient human conversation including human-to-human speech is occurring, and an interruption determining circuit configured to determine whether to cause the computer speech output unit to output the computer speech based on a status of the human conversation.

Abstract: The present disclosure provides a dialogue system and a method for controlling thereof. The dialogue system may include: an input processor configured to authenticate a user and receive new input information and new state information of the user; a storage configured to store existing state information of the user, existing input information, and available services; a controller configured to identify a service based on the new input information and the existing input information, and to identify the service based on the new state information of the user and the existing state information of the user, wherein the service is configured to fit needs of the user; and an output processor configured to determine a service format based on the new input information and the new state information of the user, wherein the service format is regarding ways to provide the service to the user.

Abstract: Provided is a method for determining access permission for a beamforming computing device communicating with a beamforming transceiver. The method includes obtaining, at a central control system, location information from an inter-zone sensor, wherein the inter-zone sensor is configured to monitor and determine a location for the beamforming computing device as the beamforming computing device nears a boundary between a first access zone and a second access zone; accessing, by a storage device of the central control system, a rule to determine whether the beamforming computing device is permitted to operate in the second access zone; determining whether the beamforming computing device is permitted to operate in the second access zone based on the rule; and executing, by a rules engine of the central control system, a first command to the inter-zone sensor to instruct a beamforming transceiver in the second zone to initiate communication with the beamforming computing device.

Abstract: A sound recognition device includes a collecting module, an extracting module connected with the collecting module, a training module, a storage module, a decoding module and a processor module. The collecting module is for receiving sound information of a specific target and a target to be measured. The extracting module is used for extracting sound characteristics of the specific target and the target to be measured. The training module is connected with the extracting module. Regard the sound characteristics of the sound information of the specific target and the target to be measured as input data of a hidden vector state (HVS) model. The storage module is connected with the training module. The decoding module is used for proceeding a language decoding procedure on sound information of the target to be measured. The processor module is connected with the training module, the storage module and the decoding module.

Abstract: An automated bot is customized for a Point-Of-Sale (POS) terminal and processed on the POS terminal. The bat has access to and can control peripheral devices of the POS terminal. The bat providing transactional and, in some embodiments, non-transactional assistance to a user operating the POS terminal.

Abstract: A method for selecting an optimal language model weight (LMW) used to perform automatic speech recognition, including decoding test audio into a lattice using a language model; analyzing the lattice using a first LMW of a plurality of LMWs to determine a first plurality of best paths; analyzing the lattice using a second LMW of the plurality of LMWs to determine a second plurality of best paths; determining a first best path change rate (BCPR) corresponding to the first LMW based on a number of best path changes between the first plurality of best paths and the second plurality of best paths; and determining the first LMW to be the optimal LMW based on the first BCPR being a lowest BCPR from among a plurality of BCPRs corresponding to the plurality of LMWs.

Abstract: A method rewrites a text message according to an emotional state of a sender of the text message while originally writing the text message. An electronic chat session monitoring device intercepts a current text message from an electronic chat session, where the current text message is generated by an initial sender at a sending device. The electronic chat session monitoring device receives a current photo, of the initial sender of the current text message, that depicts the initial sender while generating the current text message. The electronic chat session monitoring device determines that the emotional state of the initial sender, as evidenced by the current photo, is incongruous with a content of the current text message, and rewrites text in the current text message to comport with the emotional state of the initial sender while generating the current text message.

Abstract: An object searching method is disclosed. The object searching method includes the following operations: receiving an user message; analyzing an object name from the user message; obtaining a locator corresponding to the object name according to a locator mapping table; detecting a locator distance and a locator direction of the locator; generating a description string according to the locator distance, the locator direction, and a feature direction map; generating a voice message according to the description string and the object name; and broadcasting the voice message.

Abstract: A dialog device for executing a conversation with a user using a conversational sentence generated from content information is provided. The dialog device includes an information acquisition unit that acquires the content information from an information source, and changes the content information used in generation of the conversational sentence, and continues the conversation with the user. The dialog device sets multiple attribute information pieces with respect to specific content information used in generation of the conversational sentence. The dialog device controls the information acquisition unit to acquire other content information, having at least a part of attribute information pieces equal to the specific content information, as a candidate used in generation of the conversational sentence next to the specific content information.

Abstract: A communication apparatus for vehicle-to-X communication (V2X communication), including: a first V2X interface for transmitting and/or receiving vehicle-to-X messages by a first wireless communication technology, a second V2X interface for transmitting and/or receiving vehicle-to-X messages by a second wireless communication technology. Wherein the apparatus is configured to transmit information, which is received with a vehicle-to-X message by the first interface, by the second interface. The information received or respectively to be transmitted can be expediently had by at least one appropriate vehicle-to-X message received or respectively to be transmitted. A corresponding method as well as the use of the apparatus is also provided.

Abstract: A device monitors audio data for a predetermined and/or user-defined wakeword. The device detects an error in detecting the wakeword in the audio data, such as a false-positive detection of the wakeword or a false-negative detection of the wakeword. Upon detecting the error, the device updates a model trained to detect the wakeword to create an updated trained model; the updated trained model reduces or eliminates further errors in detecting the wakeword. Data corresponding to the updated trained model may be collected by a server from a plurality of devices and used to create an updated trained model aggregating the data; this updated trained model may be sent to some or all of the devices.

Abstract: An interactive apparatus includes: acquisition means for acquiring profile information in which a topic in a user's speech and the number of predetermined parts of speech of words included in the speech are associated with each other; topic selection means for setting the probability that the topic is selected in such a way that topics whose numbers of predetermined parts of speech are larger are selected with a higher probability from among topics set in the profile information based on the profile information acquired by the acquisition means, and selecting the topic in accordance with the probability of the selection that has been set; and response generation means for generating a response to the user based on the topic that has been selected by the topic selection means.

Abstract: A dialogue system for a vehicle may include: a storage configured to store vehicle state information and driving environment information; an input processor configured to acquire an utterance from a user and to extract an action corresponding to the utterance when it is identified that the utterance includes user state information; a dialogue manger configured to acquire a parameter value of a condition determination parameter used to determine whether the action corresponding to the utterance is executable from the storage, to determine an action to be executed based on the parameter value of the condition determination parameter, and to acquire a parameter value of an action parameter used to execute the determined action from the storage; and a result processor configured to generate a response to execute the determined action using the acquired parameter value of the action parameter.

Abstract: Disclosed are a segmented sentence recognition method and device for a human-machine intelligent question-answer system. One particular embodiment of the method includes: receiving a current sentence input by a user; inputting the current sentence into a pre-trained segmented sentence recognition model to obtain a first probability of the current sentence being a complete sentence, wherein the segmented sentence recognition model is used for determining the first probability according to a probability corresponding to a Chinese language model of the current sentence and a probability corresponding to a recurrent neural network language model; and if the first probability is greater than a pre-set first threshold value, determining the current sentence to be a complete sentence. In the embodiment, a Chinese language model and a recurrent neural network language model are merged to obtain a segmented sentence recognition model for determining a probability of a current sentence being a complete sentence.

Abstract: Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.

Abstract: A system for authenticating a first entity. The system comprises a storage component for storing a trained electronic-metric factor, a sensor for receiving an electronic-metric input from the first entity, an analysis component associated with a second entity for determining a first relationship between the trained electronic-metric factor and any electronic-metric input, and an authentication component for authenticating the first entity responsive to the first relationship.

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: An electronic device and a method for predicting a response are provided. The electronic device includes a display and a processor configured to receive at least one message, identify at least one contextual category of the at least one message, predict at least one response for the at least one message from a language model based on the at least one contextual category, and control the display to display the at least one predicted response.

Abstract: Aspects of the present disclosure relate to training a conversational agent. A conversational agent is initiated with a set of atomic operators, each atomic operator having one or more atomic operator rules for executing operations. A natural language input is received from a user on a conversational interface. A determination is made whether the natural language input maps to an existing script by referencing a rules engine. In response to a determination that the natural language does not map to an existing script, training is requested from the user. Training is then received from the user which maps the natural language input to a script. A mapping rule which maps the natural language input to the script is stored, and the script is executed.

Abstract: Smart speaker mechanisms are provided for processing audio sample data captured by the audio capture device is provided. The mechanisms capture one or more audio samples from a monitored environment and store the captured one or more audio samples in the audio sample buffer. The one or more captured audio samples are analyzed to determine whether the one or more captured audio samples represent a potential wake sound for initiating a responsive action by the smart speaker device. The potential wake sound is a variable sound determined to not be a normal ambient sound of the monitored environment. In response to determining that the one or more captured audio samples represent a potential wake sound for initiating a responsive action by the smart speaker device, the mechanisms initiate performance of the responsive action by the smart speaker device.

Abstract: A system, method and computer-readable storage device provides an improved speech processing approach in which hyper parameters used for speech recognition are modified dynamically or in batch mode rather than fixed statically. The method includes estimating, via a model trained on audio data and/or metadata, a set of parameters useful for performing automatic speech recognition, receiving speech at an automatic speech recognition system, applying, by the automatic speech recognition system, the set of parameters to processing the speech to yield text and outputting the text from the automatic speech recognition system.

Abstract: Disclosed is an artificial intelligence voice recognition apparatus including: a microphone; a controller configured to process a voice input received through the microphone; and a display configured to display information corresponding to each stage of a procedure of processing the voice input. Accordingly, it is possible to provide a user with diverse information according to a voice recognition process.

Abstract: For dynamic wake word identification, a processor identifies a temporary wake word based on a first response. The processor further identifies one or more content tags from the first response. The processor identifies a second query in response to receiving the temporary wake word and a first content tag, without receiving a permanent wake word.

Abstract: Methods, systems, and apparatus, including computer programs stored on a computer-readable storage medium, for asynchronous execution of client requests. In some implementations, data indicating a user request to a digital assistant is received. An action corresponding to the user request is determined. It is determined that the action is classified as an action to be performed asynchronously to the user request. A confirmation message is sent, for output, and the action is performed asynchronously to the user request.

Abstract: An electronic device includes a microphone that receives an audio signal that includes a spoken trigger phrase, and a processor that is electrically coupled to the microphone. The processor measures characteristics of the audio signal, and determines, based on the measured characteristics, whether the spoken trigger phrase is acceptable for trigger phrase model training. If the spoken trigger phrase is determined not to be acceptable for trigger phrase model training, the processor rejects the trigger phrase for trigger phrase model training.

Abstract: A sound collection apparatus includes: a sound collection unit including a microphone configured to collect sound; and a recording unit configured to record a personal dictionary used in voice recognition processing at dictation of voice collected by the sound collection unit. The sound collection apparatus further includes: a control unit configured to control provision of the personal dictionary to an information processing apparatus configured to execute dictation of voice collected by the sound collection unit; and a communication unit configured to transmit voice collected by the sound collection unit to the information processing apparatus and transmit, under control of the control unit, the personal dictionary to the information processing apparatus. This configuration achieves improved voice recognition performance even when a computer other than an exclusively used personal computer is used.

Abstract: Embodiments of the specification disclose a risk address identification method and apparatus, and an electronic device. The risk address identification method includes: acquiring an address word sequence corresponding to an input address; determining an address word in the address word sequence, the determined address word matching a risk word corresponding to a risk address; generating an observation sequence corresponding to the address word sequence according to the determined address word; processing the observation sequence using a hidden Markov model obtained based on semantics learning before and after address words, to obtain a decision vector, wherein the decision vector represents probabilities of the risk address being matched by address words contained in the address word sequence; and identifying whether the input address is a risk address by making a classification decision on the decision vector.

Abstract: Systems and methods for searching for a media asset are described. In some aspects, the system includes control circuitry that receives a first search query from a user. The control circuitry identifies media assets related to the first search query from a content database. The control circuitry receives a second search query following the first search query. The control circuitry determines whether a media asset from the media assets is related to the second search query. In response to determining that less than a threshold number of media assets from the media assets are related to the second search query, the control circuitry transmits an instruction requesting the user to repeat the second search query. The control circuitry receives a third search query related to the first search query. The control circuitry determines a media asset from the media assets that is related to the third search query.

Abstract: Techniques for implementing multiple wakeword detectors on a single device are described. A digital signal processor (DSP) of the device may implement a wakeword detection component to detect when captured speech includes a wakeword. A companion application installed on the device may implement a wakeword detection component trained using speech of a user of the device. If the DSP's wakeword detection component detects a wakeword in speech, the companion application's wakeword detection component may be used to determine whether the wakeword was spoken by the user of the device. If the companion application's wakeword detection component determines the user spoke the wakeword, audio data representing the speech may be sent to at least one server(s) for processing.