Abstract: Systems and methods are provided for training of an Automatic Speech Recognition (ASR) model during runtime of a transcription system, the system includes a background processor configured to operate with the transcription system to display a speech-to-text sample of an audio segment of a cockpit communication with an identifier which is converted using an ASR model wherein the background processor receives a response by a user during runtime of the transcription system and display of the speech-to-text sample and causes a change to the identifier to either a positive or negative attribute upon a determination of the correctness of a conversion process of the speech-to-text sample using the ASR model by review of a display of the content of the speech-to-text sample; and to train the ASR model based on information associated with the content of the speech-to-text sample in accordance with the response by the user.

Abstract: A voice recognition system in an aircraft is provided. The voice recognition system includes: a voice recognition controller configured to receive a voice command from a flight crew member voice interface, convert the voice command to an avionics system command, and forward the avionics system command to an avionics system for execution. The voice recognition system further includes an application controller configured to: receive the avionics system command that has been converted from the voice command; determine whether the avionics system command can be performed; cause the avionics system command to be performed when it is determined that the avionics system command can be performed; and when it is determined that the avionics system command cannot be performed, generate a message that provides a reason why the avionics system command cannot be performed and cause the message to be displayed on a display device and/or annunciated on an aural device.

Abstract: For example, a BT audio device may be configured to, during a passphrase-detection mode, monitor an audio input of the BT audio device to detect whether the audio input includes a voice signal, the passphrase-detection mode configured for detection of a predefined user passphrase to indicate a voice command to be provided from a user of the BT audio device; based on a determination that the audio input does not include the voice signal, transmit one or more null-data packets to a BT device over a BT wireless communication link between the BT audio device and the BT device; and, based on a determination that the audio input includes the voice signal, transmit one or more data packets to the BT device over the BT wireless communication link, wherein a payload of the one or more data packets includes audio data based on the audio input.

Abstract: A method for generating query response comprising receiving, by a processor, an input query from a first user; performing, by the processor, query parsing on the input query to generate a parsed query; determining, by the processor, a query type associated with the parsed query; for the query type being determined as initial query, performing: generating, by the processor, a first follow-up query to the input query based on the parsed query, and generating, by the processor, responses to the parsed query and the first follow-up query; and for the query type being determined as follow-up query to a previous query entered by a second user, performing: performing, by the processor, learning of a query sequence from the previous query to the input query, and generating, by the processor, responses to the parsed query and a second follow-up query.

Abstract: Provided is a system for feedback-improved automatic solving of production facility related tasks, including: an input interface being adapted to receive production facility related data; a semantic data enhancement module being adapted to generate semantically enhanced data based on the production facility related data; a semantic-based reasoning module being adapted to automatically provide an explainable artificial intelligence model, using the semantically enhanced data, wherein the artificial intelligence model relates to a predetermined production facility related task; a user interaction interface being adapted to output explanation data regarding the explainable artificial intelligence model to a user; and a feedback module adapted to receive feedback from the user in response to the outputted explanation data and adapted to adjust the semantic-based reasoning module and/or the user interaction interface based on the received feedback.

Abstract: Text independent speaker recognition models can be utilized by an automated assistant to verify a particular user spoke a spoken utterance and/or to identify the user who spoke a spoken utterance. Implementations can include automatically updating a speaker embedding for a particular user based on previous utterances by the particular user. Additionally or alternatively, implementations can include verifying a particular user spoke a spoken utterance using output generated by both a text independent speaker recognition model as well as a text dependent speaker recognition model. Furthermore, implementations can additionally or alternatively include prefetching content for several users associated with a spoken utterance prior to determining which user spoke the spoken utterance.

Abstract: Example techniques involve a control hierarchy for a “smart” home having smart appliances and related devices, such as wireless illumination devices, home-automation devices (e.g., thermostats, door locks, etc.), and audio playback devices, among others. An example home includes various rooms in which smart devices might be located. Under the example control hierarchy described herein and referred to as “home graph,” a name of a room (e.g., “Kitchen”) may represent a smart device (or smart devices) within that room. In other words, from the perspective of a user, the smart devices within a room are that room. This hierarchy permits a user to refer to a smart device within a given room by way of the name of the room when controlling smart devices within the home using a voice user interface (VUI) or graphical user interface (GUI).

Abstract: A remote control for generating output signals apt at controlling one or more electronic devices includes a sound transducer, a speech recognition unit for recognizing voice commands, a memory for storing information relative to available content of the one or more electronic devices and a control signal generating and receiving unit for generating control signals corresponding to the voice commands for controlling the one or more electronic devices.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include generating a content page and selecting an annotation container for the content page. The operations may include configuring the annotation container and inputting content into the annotation container. The operations may include submitting at least one attribute to the annotation container to associate the attribute with the content. The operations may include including the content and the at least one attribute in container data and extracting a model from the container data. The operations may include importing the model into a dialog skill and embedding the dialog skill into a user interface.

Abstract: Embodiments of the disclosure generally relate to a dialog system allowing for automatically reactivating a speech acquiring mode after the dialog system delivers a response to a user request. The reactivation parameters, such as a delay, depend on a number of predetermined factors and conversation scenarios. The embodiments further provide for a method of operating of the dialog system. An exemplary method comprises the steps of: activating a speech acquiring mode, receiving a first input of a user, deactivating the speech acquiring mode, obtaining a first response associated with the first input, delivering the first response to the user, determining that a conversation mode is activated, and, based on the determination, automatically re-activating the speech acquiring mode within a first predetermined time period after delivery of the first response to the user.

Abstract: Systems, methods, and storage media for performing actions in response to a determined spoken command of a user are disclosed.

Abstract: Embodiments of the present disclosure provide an information input method, a system of a cloud input method and a client, where the method includes: generating an input method startup instruction according to received indication information, where the indication information is generated when a focus of an information input box is acquired; sending the input method startup instruction, where the input method startup instruction is used to startup a local input method; receiving text content, where the text content is content input by using the local input method; and submitting the text content to the information input box for display. According to the embodiments of the present disclosure, the local input method of the client can be called through the input method startup instruction, and a user uses the local input method commonly used by the client to input information, which greatly improves convenience of operations.

Abstract: Disclosed are a vehicle control method and an intelligent device for controlling a vehicle. A vehicle control method according to an embodiment of the present disclosure comprises: acquiring a user request; updating the user request so as to be recognized by an application providing a service related to the user request, and providing the updated user request to the application; and providing the service through the application. Accordingly, the present invention can accurately and promptly recognize words in various forms, included in a user request, thereby providing a comparatively accurate service in accordance with the user request. One or more of an autonomous driving vehicle and an intelligent computing device of the present disclosure may be linked to an artificial intelligence module, a drone (unmanned aerial vehicle, UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G services, and the like.

Abstract: A voice wakeup method and a device are provided. The method includes: receiving, by a third-party device, wakeup messages sent by at least two electronic devices, where the wakeup message includes wakeup keyword energy information used to indicate a wakeup keyword energy value, and the wakeup keyword energy value; normalizing wakeup keyword energy values based on ambient sound energy and/or sound collection capabilities of devices, to obtain at least two normalized wakeup keyword energy values; and based on the at least two normalized wakeup keyword energy values, sending a wakeup permission instruction to a first electronic device in the at least two electronic devices, and sending a wakeup prohibition instruction to another electronic device other than the first electronic device, where a normalized wakeup keyword energy value of the first electronic device is a maximum value. This helps improve accuracy of waking up a device nearby in a multi-device scenario.

Abstract: An assistance system includes an assistance device configured to assist movement of a care receiver; a microphone provided on the assistance device; a speech analyzer configured to analyze speech of at least one of a caregiver or the care receiver included in sound data acquired by the microphone and acquire information related to an action; an echo analyzer configured to analyze an echo included the sound data and acquire information related to a location; and an action history information generator configured to generate action history information of at least one of the caregiver or the care receiver based on the information related to the action and the information related to the location.

Abstract: Domain-specific parameters may be used for tuning speech processing. A pre-trained transformer-based language model may train domain-specific parameters using domain-specific unlabeled text data. This domain-specific parameters can then be appended to candidate texts produced by a speech model on received speech data and input to the transformer-based language model to score the candidate texts. The scores of the candidate texts determined using the pre-trained transformer-based language model can then be used to select a candidate text for further speech processing.

Abstract: A method includes: in response to identifying a primary user and corresponding Primary AI Assistant for a meeting, receiving by the Primary AI Assistant a confirmation to enroll at least one user personal digital assistant (PDA) of a respective one of at least one user; prompting the at least one user to provide descriptive information associated with the respective user PDA; connecting the at least one user PDA to the Primary AI Assistant internally by the Primary AI Assistant using the descriptive information for submitting requests; identifying by the Primary AI Assistant keywords and phrases received from the at least one user or primary user in the meeting; determining by the Primary AI Assistant a scheduling item based on the identified keywords and phrases; and automatically providing by the Primary AI Assistant the scheduling item to at least one user PDA corresponding to the scheduling item using the descriptive information.

Abstract: A method of controlling an engagement state of an agent during a human-machine dialog is provided. The method can include receiving a spoken request that is a conditional locking request, wherein the conditional locking request uses a natural language expression to explicitly specify a locking condition, which is a predicate, storing the predicate in a format that can be evaluated when needed by the agent, entering a conditionally locked state in response to the conditional locking request, in the conditionally locked state, receiving a multiplicity of requests without a need for a wakeup indicator, and for a request from the multiplicity of requests evaluating the predicate upon receiving the request, and processing the request if the predicate is true.

Abstract: Disclosed are methods, systems, and machine-readable mediums which provide for customer chatbots that detect a customer handoff condition and in response, transferring the customer to a communication session with a live agent. The handoff condition may comprise an inability to understand the customer, an inability to answer the customer's question, expressions of frustration or anger on the part of the customer, a customer's express request to be transferred, or the like. The live agent may receive a complete history of the conversation with the chatbot so that the customer does not have to repeat him or herself to the live agent. The chatbot chat session may be linked to a social networking account of the customer and may take place in association with a social networking profile page of the company.

Abstract: A method and system for controlling response to a voice-command utterance. An example method includes a computing system that is associated with the first device carrying out operations upon the first device receiving the voice-command utterance. The operations include (a) making a determination of whether any of one or more second devices received the voice-command utterance before the first device received the voice-command utterance and (b) controlling whether the computing system will trigger an action in response to the first device receiving the voice-command utterance, with the controlling being based on the determination of whether any of the one or more second devices received the voice-command utterance before the first device received the voice-command utterance. In an example implementation, the action could be controlling operation of a control target such as one or more lights.

Abstract: Disclosed is an electronic device. The electronic device includes a processor configured to execute one or more instructions stored in a memory to: control a receiver to receive a speech signal; determine whether the received speech signal includes speech signals of a plurality of different speakers; when the received speech signal includes the speech signals of the plurality of different speakers, detect feature information from a speech signal of each speaker; determine relations between pieces of speech content of the plurality of different speakers, based on the detected feature information; determine a response method based on the determined relations between the pieces of speech content; and control the electronic device such that an operation of the electronic device is performed according to the determined response method.

Abstract: An electronic device and method for providing an on-device AI service are provided herein. The electronic device includes an input module configured to receive a command or data; a display module; a memory storing a first application; and a processor configured to receive, from the input module or the display module, a user request, while the first application is executed, determine content data associated with the user request, generate request information corresponding to the user request based on the content data, determine a second application to process the user request, and transmit the request information to the second application.

Abstract: The following relates generally to voice assisted healthcare. In some embodiments, a digital assistant receives audio data, and determines an intent from the audio data. The digital assistant may then match the determined intent to a flow of a set of flows, where the set of flows may include at least one of: (i) submitting a prescription, (ii) refilling a prescription, (iii) changing a pickup location, (iv) requesting a status update for a prescription, or (v) initiating a pharmacy chat session. The matched flow of the set of flows may then be executed.

Abstract: Systems, methods, and storage media for communicating with connected devices are disclosed. Exemplary implementations may: identify one or more traits for a connected device; receive an action request, wherein the action request corresponds to a first desired state of the connected device; receive a trait configuration for the one or more traits; calculate a second desired state for the connected device, wherein the second desired state is calculated based on one or more of the action request and trait configuration for the connected device; and at least one of transmit a first message to the connected device, including an indication of the first or the second desired state, or transmit a second message, including an indication of an estimated state, to the first computing device.

Abstract: An intent recognition method having a self-learning capability includes the following steps: acquiring a user expression, and recognizing a voice as a corresponding text; performing preliminary intent recognition on the user expression, and outputting candidate intents; acquiring historical data feature parameters of the candidate intents; on the basis of a pre-set rule strategy, deciding whether to directly output a final recognized intent, and on the basis of the feature parameters of each intent, performing rule computation, and outputting a final recognized intent; submitting prediction data of the final recognized intent and the candidate intents from the intent recognition process to a self-learning system, and performing self learning and indicator parameter data updating. The present disclosure is able to perform self learning on the basis of the feature distribution in historical data of intent recognition and dynamically adjust intent recognition strategies.

Abstract: A speech detection unit detects a speech in communication based on output values of microphones of a plurality of wearable terminals, and identifies a wearable terminal corresponding to the detected speech. A speech period detection unit detects for each speech a start timing of the speech and an end timing thereof. An evaluation-value calculation unit calculates, for each speech detected by the speech detection unit, an evaluation value for the speech based on an output value of an acceleration sensor of a wearable terminal other than the wearable terminal corresponding to the speech in an evaluation period from a first timing, which is at or later than the start timing of the speech and earlier than the end timing of the speech, to a second timing, which is later than the end timing of the speech.

Abstract: Recommending one or more relevant skills to a user that are appropriate for the user's current context is provided. A machine learning contextual skills model is trained on data associated with skills that are invoked by the particular user and by various users and context data that defines characteristics of the context of the users, the users' computing devices, and the users' environments in association with the invoked skills. Responsive to a trigger event associated with the user and a computing device, current context data and user data is collected and passed to the contextual skills system. The contextual skills model is applied to the collected data and generates a ranked list of skills. One or more top-ranking skills are selected and provided to the user as one or more skill recommendations that are determined to be relevant to the user and relevant to the user's current context.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for transferring dialog sessions between devices using deep links. The dialog sessions can correspond to interactions, mediated by an automated assistant, between a user and a third party application. During the dialog session, a user can request that the dialog session be transferred to a different device, for example, to interact with the third party application through a different modality. In response, the automated assistant and/or the third party application can generate a link that can be transferred to the transferee device to allow the transferee device to seamlessly take over the dialog session. In this way, computational resources and electrical power can be preserved by not requiring a recipient device to re-process natural language inputs previously provided during the dialog session.

Abstract: A device and method for providing a recommended sentence related to an utterance input of a user are provided. The method, performed by the device for providing a voice assistant service, includes determining whether the utterance input is a single utterance input; obtaining application history data related to the utterance input from among application history data representing an execution history of one or more applications executed by the user in the device when the utterance input is the single utterance input; generating the recommended utterance sentence related to the utterance input by using the utterance input and the obtained application history data; and outputting the generated recommended utterance sentence.

Abstract: A computer implemented method is provided for automatically determining a response to an input query. The method includes searching at a first stage a data repository using the input query. The data repository is configured to store historical queries and their corresponding responses. The search is adapted to determine a plurality of historical queries related to the input query and historical responses corresponding to the related historical queries. The method also includes clustering the plurality of historical responses into one or more response groups, where each response group includes one or more similar historical responses. The method additionally includes searching at a second stage a content management system (CMS) to determine if there is at least one similar response to at least one historical response in each response group. The CMS is configured to store standard responses to anticipated queries.

Abstract: The disclosure provides a method for generating a dialogue. The method includes: obtaining an input sentence; determining a type of a task-based response sentence that is to be generated, by updating a current dialogue state based on the input sentence; generating the task-based response sentence by inputting the input sentence into a task-based dialogue response generator; and determining the task-based response sentence as a target response sentence in response to the type of the task-based response sentence being a designated type.

Abstract: An agent automation system includes a memory configured to store a reasoning agent/behavior engine (RA/BE) including a first persona and a current context and a processor configured to execute instructions of the RA/BE to cause the first persona to perform actions comprising: receiving intents/entities of a first user utterance; recognizing a context overlay cue in the intents/entities of the first user utterance, wherein the context overlay cue defines a time period; updating the current context of the RA/BE by overlaying context information from at least one stored episode associated with the time period; and performing at least one action based on the intents/entities of the first user utterance and the current context of the RA/BE.

Abstract: The present disclosure generally relates to using voice interaction to access call functionality of a companion device. In an example process, a user utterance is received. Based on the user utterance and contextual information, the process causes a server to determine a user intent corresponding to the user utterance. The contextual information is based on a signal received from the companion device. In accordance with the user intent corresponding to an actionable intent of answering the incoming call, a command is received. Based on the command, instructions are provided to the companion device, which cause the companion device to answer the incoming call and provide audio data of the answered incoming call. Audio is outputted according to the audio data of the answered incoming call.

Abstract: A display device according to one embodiment of the present invention comprises an input unit, a storage unit, a display unit for displaying a menu for providing at least one function, and a control unit, which generates a user pattern, including function information corresponding to an execution command and information about the time at which the execution command was received, when receiving the execution command from a user, controls the storage unit so as to store the generated user pattern, reconfigures the menu on the basis of the user pattern, and controls the display unit so as to display the reconfigured menu.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing assistance for customer service agents are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, customer interaction data that reflects an interaction between a first user and a second user. The actions further include receiving, by the computing device, a customer summary file that reflects characteristics of the first user. The actions further include, based on the customer interaction data and the customer summary file, determining, by the computing device, instructions for the second user to continue interacting with the first user during the interaction between the first user and the second user. The actions further include, based on determining the instructions, providing, for output to the second user, the instructions for the second user to continue interacting with the first user.

Abstract: Various arrangements are detailed herein related to managing video recording based on spoken commands. A system receives a video stream from a video camera and analyzes a field of view in the received video stream to determine a location for one or more identified or potential users. The system can beamform audio from microphones of a home assistant device based on the location of the one or more identified or potential users. The system adjusts an audio output based on the location of the one or more identified or potential users, receives a spoken command from the one or more identified or potential users, and outputs a response to the spoken command.

Abstract: The present disclosure provides systems and methods that generating health diagnostic information from an audio recording. A computing system can include a machine-learned health model comprising that includes a sound model trained to receive data descriptive of a patient audio recording and output sound description data. The computing system can include a diagnostic model trained to receive the sound description data and output a diagnostic score. The computing system can include at least one tangible, non-transitory computer-readable medium that stores instructions that, when executed, cause the processor to perform operations. The operations can include obtaining the patient audio recording; inputting data descriptive of the patient audio recording into the sound model; receiving, as an output of the sound model, the sound description data; inputting the sound description data into the diagnostic model; and receiving, as an output of the diagnostic model, the diagnostic score.

Abstract: Systems and processes for providing a virtual assistant service are provided. In accordance with one or more examples, a method includes receiving, from an accessory device communicatively coupled to the first electronic device, a representation of a speech input representing a user request. The method further includes detecting a second electronic device and transmitting, from the first electronic device, a representation of the user request and data associated with the detected second electronic device to a third electronic device. The method further includes receiving, from the third electronic device, a determination of whether a task is to be performed by the second electronic device in accordance with the user request; and in accordance with a determination that a task is to be performed by the second electronic device, requesting the second electronic device to performed the task in accordance with the user request.

Abstract: Systems and methods for optimizing network microphone devices using noise classification are disclosed herein. In one example, individual microphones of a network microphone device (NMD) detect sound. The sound data is analyzed to detect a trigger event such as a wake word. Metadata associated with the sound data is captured in a lookback buffer of the NMD. After detecting the trigger event, the metadata is analyzed to classify noise in the sound data. Based on the classified noise, at least one performance parameter of the NMD is modified.

Abstract: Systems and methods for identifying audio events in one or more audio streams include the use of a cascade audio spotting system (such as a cascade keyword spotting system (KWS)) to reduce power consumption while maintaining a desired performance. An example cascade audio spotting system may include a first module and a high-power subsystem. The first module is to receive an audio stream from one or more audio streams, process the audio stream to detect a first target sound activity in the audio stream, and provide a first signal in response to detecting the first target sound activity in the audio stream. The high-power subsystem is to (in response to the first signal being provided by the first module) receive the one or more audio streams and process the one or more audio streams to detect a second target sound activity in the one or more audio streams.

Abstract: Recommending an automated assistant action for inclusion in an existing automated assistant routine of a user, where the existing automated assistant routine includes a plurality of preexisting automated assistant actions. If the user confirms the recommendation through affirmative user interface input, the automated assistant action can be automatically added to the existing automated assistant routine. Thereafter, when the automated assistant routine is initialized, the preexisting automated assistant actions of the routine will be performed, as well as the automated assistant action that was automatically added to the routine in response to affirmative user interface input received in response to the recommendation.

Abstract: An occupancy tracking device configured to receive a plurality of sound samples over a predetermined time period. The device is further configured to compute an audio signature for each sound sample. The device is further configured to populate entries in the voice data log for the sound samples, to identify one or more clusters based on an audio signature that is associated with the populated entries, and to determine a number of clusters that are identified. The device is further configured to determine a predicted occupancy level based on the number of clusters that are identified and to control a Heating, Ventilation, and Air Conditioning (HVAC) system based on the predicted occupancy level.

Abstract: Systems and methods for identifying content corresponding to a language are provided. Language spoken by a first user based on verbal input received from the first user is automatically determined with voice recognition circuitry. A database of content sources is cross-referenced to identify a content source associated with a language field value that corresponds to the determined language spoken by the first user. The language field in the database identifies the language that the associated content source transmits content to a plurality of users. A representation of the identified content source is generated for display to the first user.

Abstract: The present disclosure is directed techniques for executing a task or service using a virtual agent. A method includes: executing, using a virtual agent, one or more tiers of a plurality of tiers of machine learning analysis to identify a desired action to be performed based on a user command, the user command being received from an external computing device; responsive to the one or more tiers of the plurality of tiers of machine learning analysis identifying a plurality of actions associated with the user command, determining a series of inquiries to present via the external computing device, wherein each inquiry of the series of inquiries is selected based on a number of actions associated with each inquiry, and wherein each subsequent inquiry in the series of inquires is based on a user response to a preceding inquiry; identifying, based on responses to the series of inquiries, the desired action to be performed; and executing the desired action to be performed.

Abstract: Systems and methods are disclosed configured to detect impairment issues, and via an interlock device, inhibit operation of an item of equipment when impairment is detected. The interlock device may comprise a solid state relay, an electromechanical relay, and/or a solenoid. The interlock device may perform power isolation and/or may use a mechanism, such as a rotating cam or gear, to immobilize a control and/or other components. Based on detected impairment, a determination is made as to whether the interlock is to be activated or deactivated.

Abstract: In a first aspect of the invention, it is claimed a computer-implemented method for assisting the movement of a visually impaired user by means of a wearable device 1, comprising the following steps: S1—Acquiring data from the environment of the visually impaired user S2—Fusing the acquired data, creating, repeatedly updating of a Live Map S3—Determining, repeatedly updating and storing, of at least one navigation path together with associated navigation guiding instructions for the visually impaired user to navigate from the current position of the visually impaired user to a point of interest, repeatedly selecting one preferred navigation path from the at least one navigation path, and repeatedly sending to the visually impaired user the preferred navigation path, together with associated navigation guiding instructions.

Abstract: Some natural language command processing systems may handle some commands on a user device rather than sending input to another system for processing. Such a system may include an arbitration component for arbitrating between device and/or system processing. The arbitration component may execute in the system and render a device-specific decision as to whether the device will be able to process the input and/or execute the command, based on information known to the system about the device's capabilities. If the arbitration component predicts that the device will not be able to execute the command, the system may execute the command without waiting for a signal from the device. If the arbitration component predicts that the device will be able to execute the command, the system may halt processing to prevent duplicate execution.

Abstract: Systems and methods are presented herein for generating a new language understanding model, based on a user request. A user may input a root language and a locale into an application for generating a student language model. The application may generate the student language model and may identify a teacher language model related to the student language model. The application may compare data from the identified teacher language model to the student language model. The application may determine a subset of data from the teacher language model is not contained in the student language model. If the application determines at least a subset of data from the teacher language model is not in the student language model, the application may add at least the subset of data from the teacher language model to the student language model.

Abstract: A computing system for enabling a user to control a legacy application of an enterprise using voice commands includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the computing system to receive a user utterance; generate an output by analyzing the utterance using a speech-to-text application programming interface; and perform an action with respect to an element of the legacy application. A computer-implemented method includes receiving a user utterance; generating an output by analyzing the utterance using a speech-to-text application programming interface; and performing an action with respect to an element of the legacy application. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to receive a user utterance; generate an output by analyzing the utterance using a speech-to-text application programming interface; and perform an action with respect to an element of the legacy application.

Abstract: An electronic apparatus and a control method thereof are provided, which displays first voice guide information indicating voice commands available to control the electronic apparatus, and if a command to control an external device connected to the electronic apparatus is received, changes the first voice guide information and displays second voice guide information to indicating voice commands available to control the external device.