Abstract: A smartwatch includes a destination handling unit configured to issue a destination call in an elevator system of an environment. The smartwatch has an input for entering destination data as well as an output for indicating an allocated elevator of the elevator system. The smartwatch includes a navigation system including a memory with map data of the environment. The navigation system includes a position detector for detecting the location of the smartwatch within the environment, and a navigation output connected with the output. The navigation system is coupled with the destination handling unit to issue a destination call based on data of the position detector and/or for providing navigation guide data based on an issued destination call.

Abstract: Techniques for altering audio being output by a voice-controlled device, or another device, to enable more accurate automatic speech recognition (ASR) by the voice-controlled device. For instance, a voice-controlled device may output audio within an environment using a speaker of the device. While outputting the audio, a microphone of the device may capture sound within the environment and may generate an audio signal based on the captured sound. The device may then analyze the audio signal to identify speech of a user within the signal, with the speech indicating that the user is going to provide a subsequent command to the device. Thereafter, the device may alter the output of the audio (e.g., attenuate the audio, pause the audio, switch from stereo to mono, etc.) to facilitate speech recognition of the user's subsequent command.

Abstract: Disclosed is a user-customized artificial intelligence (AI) speaker-based personalized service system using voiceprint recognition. The system is used by a small group of users. The system includes a voice recognition device that identifies each user through voice recognition and enables a voice instruction of each user to be executed, and a data processing device interconnected with the voice recognition device. The voice recognition device includes a storage unit that stores speech samples of respective registered users, a receiver that receives a first utterance of a first utterer, a determination unit that determines whether the first utterer is a registered user by comparing the first utterance of the first utterer against the speech samples of the respective registered users stored in the storage unit, and an execution that generates an instruction signal corresponding to a first instruction phrase uttered as a first voice instruction by the first utterer.

Abstract: A method for voice recognition (VR)-based task allocation and hotword detection function control for within a wireless network having a hands-free (HF) node, e.g., a motor vehicle or telematics unit thereof, and an audio gateway (AG) node such as a wireless device, includes detecting, via a first wireless chipset of the HF node, a second wireless chipset of the AG node. The wireless chipsets include respective VR engines responsive to a corresponding hotword. The method includes establishing a Bluetooth or other wireless connection between the wireless chipsets in response to detecting the second wireless chipset. The method may include automatically transmitting a disable command signal to the second wireless chipset, via the first wireless chipset, to thereby disable a hotword detection function of the second wireless chipset. The method may be recorded on a computer readable medium as instructions executable by a processor.

Abstract: An embodiment for cognitively enhancing a search query is provided. The embodiment may include receiving a voice query from a user. The embodiment may also include analyzing the voice query. The embodiment may further include identifying an object within a focus area of the user based on the voice query. The embodiment may also include determining whether the identification of the object is confident, and in response to determining the identification of the object is not confident, receiving feedback from the user. In response to determining the identification of the object is confident, the embodiment may further include generating a relationship between a word in the voice query and the identified object. The embodiment may also include delivering an enhanced response to the user based on the identified object and the received feedback.

Abstract: Disclosed is a server for supporting a communication environment between different electronic devices. The server includes a communication circuit, a memory, and a processor. The processor is electrically connected to the communication circuit and the memory. The processor is configured to receive a first voice signal transmitted from a second electronic device to a first electronic device through the communication circuit. The Processor is also configured to allow the first electronic device to transmit network connection information for connecting with the server to the second electronic device based on whether the first voice signal corresponds to a second voice signal stored in the memory.

Abstract: A voice control method, includes: acquiring a voice input information; recognizing the voice input information to obtain a voice command; based on the voice command, determining a control corresponding to the voice command by a test framework calling unit, where the test framework calling unit is not in an application program in which the control is coded; and executing a function corresponding to the control. A voice control device and a computer-executable non-volatile storage medium are further provided.

Abstract: An independent add-on automated vehicle lift gate system utilizing existing key fob authentication circuits in combination with an independent voice control system. The system uses microphones in connection with audio acquisition hardware and voice recognition hardware that actively listen for one or more voiced commands from a user outside of a vehicle. Before activating the mechanical system, which is for example the actuator of the lift gate and lock mechanism for the lift gate, the system will wait for confirmation from a separate vehicle system that monitors and notifies the vehicle lift gate system when an identification code is received from a key fob transponder located in a predetermined proximity of the vehicle, thereby authenticating the one or more voiced commands detected by the microphones.

Abstract: The present disclosure provides a method and a device of denoising a voice signal. The method portion includes the following steps: filtering out an environmental noise signal in an original input signal according to an interference signal related to the environmental noise signal in the original input signal to obtain a first voice signal; obtaining a sample signal matching the first voice signal from a voice signal sample library; and filtering out other noise signal in the first voice signal according to the sample signal matching the first voice signal, to obtain an effective voice signal. The method provided by the present disclosure may effectively filter out the environmental noise signal and other noise signal in the voice signal.

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: A processor-implemented method includes: using an encoder, determining, for each of a plurality of tokens included in an input sequence, a self-attention weight based on a token and one or more tokens that precede the token in the input sequence; using the encoder, determining context information corresponding to the input sequence based on the determined self-attention weights; and using a decoder, determining an output sequence corresponding to the input sequence based on the determined context information.

Abstract: According to an embodiment of the present invention, an artificial intelligence (AI) apparatus for performing voice control, includes a memory configured to store a voice extraction filter for extracting a voice of a registered user, and a processor to receive identification information of a user and a first voice signal of the user, to register the user using the received identification information, to extract a voice of the registered user from the received second voice signal by using the voice extraction filter corresponding to the registered user, when a second voice signal is received, and to proceed a control operation corresponding to intention information of the extracted voice of the registered user. The voice extraction filter is generated by using the received first voice signal of the registered user.

Abstract: Described are apparatus, systems, and methods that are operable to periodically detected and record a voice of a user associated with or wearing a wearable device. As described, the wearable device apparatus is configured to transition various components of the device between a low power state and an active state to determine if audio data that includes voice is detected. If voice is not detected, the components are transitioned back to the low power state, thereby conserving power of the wearable device. If voice is detected, the audio data that includes that voice is collected for further processing.

Abstract: A device may receive user personalized data and user activity data identifying tasks and actions performed by a user, and may perform natural language processing on the user personalized data and the user activity data to generate processed textual data. The device may train machine learning models based on the processed textual data to generate trained machine learning models, and may receive, from a client device, a command identifying a particular task to be performed. The device may process the command and the user activity data, with the trained machine learning models, to determine whether a particular action in the user activity data correlates with the particular task. The device may perform actions when the particular action correlates with the particular task.

Abstract: An electronic device controlling system that provides an instruction via voice for an operation of a speech recognition-capable electronic device includes a control device and a voice output device capable of communicating with the control device. The control device includes a first input unit that receives, from an operator, a first input to which a first operation instruction for the speech recognition-capable electronic device is assigned; and a transmitter that, when the first input unit receives the first input, transmits, to the voice output device, first information for communication corresponding to the first operation instruction assigned to the first input. The voice output device includes a receiver that receives the first information for communication from the control device; and an output unit that, when the receiver receives the first information for communication, outputs a first voice for the first operation instruction based on the first information for communication.

Abstract: A method for processing a voice input and a system therefor are provided. The system includes a microphone, a speaker, a processor, and a memory. The processor, in a first operation, receives a first voice input including a first wake-up keyword, selects a first response model based on the first voice input, receives a second voice input after the first voice input, processes the second voice input, using an NLU module, generates a first response based on the processed second voice input, in a second operation, receives a third voice input including a second wake-up keyword different from the first wake-up keyword, selects a second response model based on the third voice input, receives a fourth voice input after the third voice input, processes the fourth voice input, using the NLU module, and generates a second response based on the processed fourth voice input.

Abstract: The system trains a model to provide information used to provide a synthesized speech response to a voice input. The model takes as input prosodic information that may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example. The system receives a plurality of voice inputs, each associated with prosodic metric, as well as a plurality of responses, each also associated with prosodic metrics. The system trains the model based on the plurality of voice inputs, the plurality of responses, the prosodic metrics of the voice inputs, and the prosodic metrics of the responses such that the model outputs information used to generate the response. The model may also take as input user profile information, emotion metrics, and transition information to generate output. The output of the training model may be used by the system to provide synthesized speech responses having relevant prosodic character to received voice inputs.

Abstract: Implementations set forth herein relate to an automated assistant that can control graphical user interface (GUI) elements via voice input using natural language understanding of GUI content in order to resolve ambiguity and allow for condensed GUI voice input requests. When a user is accessing an application that is rendering various GUI elements at a display interface, the automated assistant can operate to process actionable data corresponding to the GUI elements. The actionable data can be processed in order to determine a correspondence between GUI voice input requests to the automated assistant and at least one of the GUI elements rendered at the display interface. When a particular spoken utterance from the user is determined to correspond to multiple GUI elements, an indication of ambiguity can be rendered at the display interface in order to encourage the user to provide a more specific spoken utterance.

Abstract: A chat console includes a chat portion and at least one portion corresponding to an enterprise system application. The chat portion displays text related to a chat interaction between the agent and a customer in real-time in an ongoing manner. The portion related to the enterprise system application displays data relevant to the chat interaction fetched from a respective enterprise system application. The agent console operatively communicates with three enterprise system applications, such that data relevant to the current chat interaction is fetched from each of the three enterprise system applications and displayed in a respective portion within the agent console.

Abstract: According to one embodiment of the present invention, a server comprises at least one communication interface, at least one processor operatively connected to the communication interface, and at least one memory operatively connected to the processor, wherein the memory store instructions configured to, when executed, cause the processor: receives, from a first electronic device, first input voice data including a first request for conducting a first task by using a second electronic device by user's utterance; determines or receives a state of the first electronic device; and provides a first external electronic device with a first response related to control of the state of the first electronic device. Various other embodiments are possible.

Abstract: The system provides a synthesized speech response to a voice input, based on the prosodic character of the voice input. The system receives the voice input and calculates at least one prosodic metric of the voice input. The at least one prosodic metric can be associated with a word, phrase, grouping thereof, or the entire voice input. The system also determines a response to the voice input, which may include the sequence of words that form the response. The system generates the synthesized speech response, by determining prosodic characteristics based on the response, and on the prosodic character of the voice input. The system outputs the synthesized speech response, which includes a more natural, relevant, or both answer to the call of the voice input. The prosodic character of the voice input and/or response may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example.

Abstract: A scalable system provides automated conversation review that can identify potential miscommunications. The system may provide suggested actions to fix errors in intelligent virtual assistant (IVA) understanding, may prioritize areas of language model repair, and may automate the review of conversations. By the use of an automated system for conversation review, problematic interactions can be surfaced without exposing the entire set of conversation logs to human reviewers, thereby minimizing privacy invasion. A scalable system processes conversations and autonomously marks the interactions where the IVA is misunderstanding the user.

Abstract: A computer-implemented method includes receiving, at a microphone of a voice-controlled device, a speech input, generating an electrical signal having a first gain level that is below a gain threshold for audible detection by a user, transmitting the electrical signal to the speaker and detecting, by the microphone, an audio signal that includes a combination of ambient noise and a probe audio signal, wherein the probe audio signal is output by the speaker based on the electrical signal. The method further includes determining a power level of the probe audio signal and determining a state of the display based on the power level of the probe audio signal.

Abstract: Various embodiments of the present disclosure relate generally to providing services to users via communication channels. More specifically, various embodiments of the present disclosure relate to systems and methods for modifying, updating, and/or changing communication channel interactions based on the tracking or listening for events within other communication channels.

Abstract: A device to process an audio signal representing input sound includes a hand detector configured to generate a first indication responsive to detection of at least a portion of a hand over at least a portion of the device. The device also includes an automatic speech recognition system configured to be activated, responsive to the first indication, to process the audio signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for cross input modality learning in a mobile device are disclosed. In one aspect, a method includes activating a first modality user input mode in which user inputs by way of a first modality are recognized using a first modality recognizer; and receiving a user input by way of the first modality. The method includes, obtaining, as a result of the first modality recognizer recognizing the user input, a transcription that includes a particular term; and generating an input context data structure that references at least the particular term. The method further includes, transmitting, by the first modality recognizer, the input context data structure to a second modality recognizer for use in updating a second modality recognition model associated with the second modality recognizer.

Abstract: A system is provided for handling errors during automatic speech recognition by leveraging past inputs spoken by the user. The system may process a user input to determine an ASR hypothesis. The system may then determine an alternate representation of the user input based on the inputs provided by the user in the past, and whether the ASR hypothesis sufficiently matches one of the past inputs.

Abstract: An application automatically composed using natural language processing. A natural language input comprising one or more application requirements is received via an interface. The natural language input is parsed to extract one or more chunks, each chunk representing one of the application requirements, and at least one of the chunks representing at least one of one or more main functionalities described by the application requirements. A coarse architecture logically arranging the main functionalities to satisfy the application requirements is inferred according to the chunks. Existing assets corresponding to the chunks are identified, each asset associated with at least one of the main functionalities. The identified assets are assembled according to the coarse architecture. The assembled assets are deployed as an application.

Abstract: Techniques for identifying certain signals sent over the CAN bus between components of a vehicle are provided herein. Specifically, certain testing maneuvers designed to engage the component of interest are provided to a technician for performing on the vehicle. The messages can be captured from the CAN bus and analyzed, using supervised machine learning algorithms, to isolate the message ids and the byte numbers so that the values of the component of interest may be observed for determining performance metrics. Once identified, these performance metrics may be used to compare with other vehicles or improve the design and performance of the vehicle.

Abstract: One embodiment provides a method, including: receiving at a digital personal assistant coupled to an information handling device, while receiving a command from a first user, an input from a second user; determining that the input provided by the second user is directed at the first user; providing an indication indicating the command is directed to the digital personal assistant; and ignoring the input provided by the second user. Other aspects are described and claimed.

Abstract: Disclosed are an intelligent voice recognizing method, a voice recognizing apparatus, and an intelligent computing device. The an intelligent voice recognizing method according to an embodiment of the present disclosure receives a voice, acquires a sequential start language uttered sequentially with a utterance language from the voice, and sets the sequential start language as an additional start language other than a basic start language when the sequential start language is recognized as a start language of a voice recognizing apparatus, thereby being able to authenticate a user and recognize a voice even through a seamless scheme voice that is uttered in an actual situation. According to the present disclosure, one or more of the voice recognizing device, intelligent computing device, and server may be related to artificial intelligence (AI) modules, unmanned aerial vehicles (UAVs), robots, augmented reality (AR) devices, virtual reality (VR) devices, and 5G service-related devices.

Abstract: A method of providing multimodal input data to client applications in a data capture device with multiple input assemblies includes: storing, in a memory of the device: a client application defining input fields; and a plurality of input profiles each containing an input field identifier and a modality identifier corresponding to one of the input assemblies. Via execution of the client application, the device controls a display to simultaneously render a plurality of the input fields; determines an active one of the rendered input fields and obtains an active field identifier of the active input field; retrieves an active one of the input profiles containing a field identifier that matches the active input field identifier; controls one of the input assemblies corresponding to the modality identifier of the active input profile to obtain input data; and populates the active input field with the obtained input data.

Abstract: A video content item may be provided to a user in a first area of a graphical user interface (GUI). Related video content items may be provided in a second area of the GUI. A selection of a control element provided in the GUI may be received where the selection of the control element indicates that the user is interested in a first audio component that is included in the first audio content item. In response to receiving the selection of the control element, a plurality of second audio components that are included in different video content items and are similar to the first audio component may be identified and the second area of the GUI may be modified to prioritize a presentation of at least one of the different video content items that includes at least one of the second audio components over a presentation of the related video content items in the second area of the GUI.

Abstract: Embodiments of the present disclosure provide a method and apparatus for recognizing speech. An embodiment of the method includes: in response to detecting a speech frame, converting the speech frame into a current text in real time; in response to there being no previously saved historical text, inputting the current text into a semantic parsing model to obtain a parsing result; in response to the parsing result including a valid intention slot, ending a speech endpoint detection to complete the recognition; and outputting an instruction corresponding to the valid intention slot.

Abstract: The present application provides a method and apparatus for human-computer interaction in a display device, and a computer device and a storage medium. The method comprises: a display device acquiring current image data of a user, and displaying multiple pieces of different candidate data in different display regions when it is detected that the user is in a squarely viewing state, so that the user browses the candidate data; and the display device identifying a target display region which is focused on, and reading candidate data corresponding to the target display region, and executing an operation corresponding to the read candidate data.

Abstract: Implementations of the present disclosure include receiving a query, the query including an expression macro (EM), processing the query to provide a raw parse tree, the raw parse tree including an initial node representative of the EM, retrieving metadata corresponding to the EM, the metadata including a definition string, replacing the initial node with a node based on the definition string to provide a consumable parse tree, and executing the query within the database system using the consumable parse tree to provide a query result.

Abstract: An autonomously motile device may be controlled by speech received by a user device. A first speech-processing system associated with the user device may determine that audio data includes a representation of a command; a second speech-processing system associated with the autonomously motile device may determine that the command should be executed by the autonomously motile device. A network connection is established between the user device and the autonomously motile device, and a device manager authorizes execution of the command.

Abstract: In some examples, natural language dialogue system perturbation testing may include identifying semantic segments for conversation data for a natural dialogue system. For each semantic segment, a perturbed variant that includes a perturbation may be generated, and forwarded to the natural dialogue system. An updated response to the perturbed variant may be obtained from the natural dialogue system. A semantic similarity may be determined between an original response to a semantic segment and the updated response, and based on the semantic similarity between the original response and the updated response, a perturbability of the natural dialogue system may be determined. A determination may be made as to whether the perturbability of the natural dialogue system is greater than a specified perturbability threshold, and if so, a training corpus that includes a failed response to a perturbed variant may be utilized to train the natural dialogue system.

Abstract: An Internet of Things (IoT) module adaptor application may be used to provide operational compatibility between a device application of an IoT device and multiple IoT modules. The IoT module adaptor application may detect that an IoT module is connected to the IoT device, in which the IoT module provides a network connectivity functionality to the IoT device. An identity of the IoT module is ascertained by the IoT module adaptor application based on identification information provided by the IoT module. The IoT module adaptor application may determine a specific combination of at least one of one or more ATtention (AT) commands or one or more application program interfaces (APIs) as stored in a software library that corresponds to the identity of the IoT module. Subsequently, the IoT module adaptor application may provide a device application of the IoT device with access to the specific combination for the device application to interact with the IoT module.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In one example process, a first instance of a digital assistant operating on a first electronic device receives a natural-language speech input indicative of a user request. The first electronic device obtains a set of data corresponding to a second instance of the digital assistant on a second electronic device, and updates one or more settings of the first instance of the digital assistant based on the received set of data. The first instance of the digital assistant performs one or more tasks based on the updated one or more settings and provides an output indicative of whether the one or more tasks are performed.

Abstract: Characteristics of a speaker are estimated using speech processing and machine learning. The characteristics of the speaker are used to automatically customize a user interface of a client device for the speaker.

Abstract: An interactive voice adapter for adaptive voice routing may establish a real-time communication session between a voice communication client and a text communication client and the voice adapter may receive the audio stream and the text information. The voice adapter may obtain adapted natural language text corresponding to the natural language audio by selectively accessing a speech-to-text service based on a selection criteria. The voice adapter may obtain adapted natural language audio corresponding to the natural language text by selectively accessing a text-to-speech service based on the selection criteria. The voice adapter may communicate the adapted natural language text to the text communication client and the adapted natural language audio to the voice communication client.

Abstract: Examples of systems and methods for voice-based navigation in one or more virtual areas that define respective persistent virtual communication contexts are described. These examples enable communicants to use voice commands to, for example, search for communication opportunities in the different virtual communication contexts, enter specific ones of the virtual communication contexts, and bring other communicants into specific ones of the virtual communication contexts. In this way, these examples allow communicants to exploit the communication opportunities that are available in virtual areas, even when hands-based or visual methods of interfacing with the virtual areas are not available.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to optimizing engagement with a display during digital assistant-performed operations in response to a received command. The digital assistant generates an overlay having user interface elements that present information determined to be relevant to a user based on the received command and contextual data. The overlay is presented over the underlying operations performed on corresponding applications to mask the visible steps of the operations being performed. In this way, the digital assistant optimizes display resources that are typically rendered useless during the processing of digital assistant-performed operations.

Abstract: Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input from a device. The NLP system may also receive one or more signals representing one or more assistants to be implemented with respect to the natural language input. The NLP system may intelligently select an assistant to be invoked with respect to the natural language input. Once the assistant is selected, the NLP system may cause content, output to a user, to have characteristics specific to the assistant.

Abstract: In order to quickly respond to a question for vehicle information from a vehicle user at a remote location and offer the user a sense of relief, a vehicle management system of the present invention comprises a telematics communication unit which is mounted on a vehicle and acquires vehicle information and, a vehicle information server which receives from the telematics communication unit the vehicle information and a time at which the vehicle information is acquired, stores the received vehicle information and time, and transmits the stored vehicle information and time to a speech processing system as a response to a question when receiving the question about the vehicle information from the speech processing system.

Abstract: A machine learning system is accessed. The machine learning system is used to translate content into a representative icon. The machine learning system is used to manipulate emoji. The machine learning system is used to process an image of an individual. The machine learning processing includes identifying a face of the individual. The machine learning processing includes classifying the face to determine facial content using a plurality of image classifiers. The classifying includes generating confidence values for a plurality of action units for the face. The facial content is translated into a representative icon. The translating the facial content includes summing the confidence values for the plurality of action units. The representative icon comprises an emoji. A set of emoji can be imported. The representative icon is selected from the set of emoji. The emoji selection is based on emotion content analysis of the face.

Abstract: A voice input apparatus inputs voice and performs control to, in a case where a second voice instruction for operating the voice input apparatus is input in a fixed period after a first voice instruction for enabling operations by voice on the voice input apparatus is input, execute processing corresponding to the second voice instruction. The voice input apparatus, in a case where it is estimated that a predetermined user issued the second voice instruction, executes processing corresponding to the second voice instruction when the second voice instruction is input, even in a case where the first voice instruction is not input.

Abstract: A vehicle-mounted device operation system, includes: an operating part that is located in a vehicle cabin, and configured to be subjected to operation for manually operating a vehicle-mounted device; a sound collector that is located in the vehicle cabin, and configured to collect speech of an occupant; and a processor configured to determine whether a command to the vehicle-mounted device is included in a content of the speech of the occupant collected by the sound collector, activate the vehicle-mounted device according to the command, when the processor determines that the command to the vehicle-mounted device is included in the content of the speech of the occupant, and highlight the operating part for the vehicle-mounted device activated by the processor.

Abstract: An apparatus and method for executing a voice command in an electronic device. In an exemplary embodiment, a voice signal is detected and speech thereof is recognized. When the recognized speech contains a wakeup command, a voice command mode is activated, and a signal containing at least a portion of the detected voice signal is transmitted to a server. The server generates a control signal or a result signal corresponding to the voice command, and transmits the same to the electronic device. The device receives and processes the control or result signal, and awakens. Thereby, voice commands are executed without the need for the user to physically touch the electronic device.