Abstract: Systems and methods for providing notifications without breaking media immersion. A notification delivery application receives notification data while a media device provides a media asset. In response to receiving the notification data while the media device provides the media asset, the notification delivery application generates a voice model based on a voice detected in the media asset. The notification delivery application converts the notification data to synthesized speech using the voice model and generates, by the media device, the synthesized speech for output at an appropriate point in the media asset based on contextual features of the media asset.

Abstract: The invention provides a content playback system comprising a playback device that is configured to detect a voice command from a user and to play content. When a voice command is received, the system is configured to analyse the voice command to determine a user intent. The system then extracts one or more entities from the voice command, wherein each of the extracted entities is of a type associated with the determined user intent. Then, based on the one or more extracted entities, the system controls the playback device. Analysis of the voice command in this manner may improve an accuracy with which a meaning of the voice command can be obtained, thereby facilitating control of the playback device.

Abstract: Systems and methods for dynamically customizing a virtual assistant are disclosed. The systems and methods can receive information associated with a conversation involving the virtual assistant; determine whether a channel switching condition for switching the conversation from a first channel to a second channel is satisfied, based on the information associated with the conversation; determine whether a language switching condition for switching the conversation from a first language to a second language is satisfied, based on the information associated with the conversation; determine whether a configuration switching condition for switching a first configuration of the virtual assistant to a second configuration of the virtual assistant is satisfied, based on the information associated with the conversation; and perform an action based on at least one of the determinations.

Abstract: Techniques are disclosed for training and/or utilizing an automatic post-editing model in correcting translation error(s) introduced by a neural machine translation model. The automatic post-editing model can be trained using automatically generated training instances. A training instance is automatically generated by processing text in a first language using a neural machine translation model to generate text in a second language. The text in the second language is processed using a neural machine translation model to generate training text in the first language. A training instance can include the text in the first language as well as the training text in the first language.

Abstract: Automatic generation of intelligent content is created using a system of computers including a user device and a cloud-based component that processes the user information. The system performs a process that includes receiving an input document and parsing the input document to generate inputs for a natural language generation model using a text analysis model. The natural language generation model generates one or more candidate presentation scripts based on the inputs. A presentation script is selected from the candidate presentation scripts and displayed. A text-to-speech model may be used to generate a synthesized audio presentation of the presentation script. A final presentation may be generated that includes a visual display of the input document and the corresponding audio presentation in sync with the visual display.

Abstract: The present invention describes the user authentication system comprising of multiple levels of security which is used to authorize the user. The system uses more than one levels of authentication process which receives the credentials from the user and authorizes them to allow access to the IoT devices which are used by the user. The connected devices represent individual targets for the cyber-criminals who 20 would hack the devices to retrieve the secure information of the users. Such insecurities about the IoT devices and the system are eliminated by using the multiple level user authentication system which is described in the present invention.

Abstract: Detecting a replay attack on a voice biometrics system comprises receiving a speech signal; forming an autocorrelation of at least a part of the speech signal; and identifying that the received speech signal may result from a replay attack based on said autocorrelation. Identifying that the received speech signal may result from a replay attack may be achieved by: comparing the autocorrelation with a reference value; and identifying that the received speech signal may result from a replay attack based on a result of the comparison of the autocorrelation with the reference value, or by: supplying the autocorrelation to a neural network trained to distinguish autocorrelations formed from speech signals resulting from replay attacks from autocorrelations formed from speech signals not resulting from replay attacks.

Abstract: In general, techniques are described for various aspects of accessing datasets. A device comprising a memory configured to store the dataset, and a processor may be configured to perform the techniques. The processor may expose a language sub-surface specifying a natural language containment hierarchy defining a grammar for a natural language as a hierarchical arrangement of a plurality of language sub-surfaces. The processor may receive a query to access the dataset, the query conforming to a portion of the natural language provided by the exposed language sub-surface. The processor may transform the query into one or more statements that conform to a formal syntax associated with the dataset, access, based on the one or more statements, the dataset to obtain a query result, and output the query result.

Abstract: Techniques to dynamically customize a menu system presented to a user by a voice interaction system are provided. Audio data from a user that includes the speech of a user can be received. Features can be extracted from the received audio data, including a vocabulary of the speech of the user. The extracted features can be compared to features associated with a plurality of user group models. A user group model to assign to the user from the plurality of user group models can be determined based on the comparison. The user group models can cluster users together based on estimated characteristics of the users and can specify customized menu systems for each different user group. Audio data can then be generated and provided to the user in response to the received audio data based on the determined user group model assigned to the user.

Abstract: The present disclosure provides method and apparatus for guiding topic in a conversation between a user and a chat engine. At least one first topic is determined. A first message is provided to the user based on the at least one first topic, to guide the conversation to the at least one first topic. A first response to the first message is received from the user. It is determined whether the first response is associated with the at least one first topic. In the case of determining that the first response is associated with the at least one first topic, at least one second topic is determined based on the at least one first topic. At least one second message is provided based at least on the at least one second topic, wherein if the at least one second topic is associated with resource or service, the at least one second message includes at least the resource or service.

Abstract: A speech to text system includes a text and labels module receiving a text input and providing a text analysis and a label with a phonetic description of the text. A label buffer receives the label from the text and labels module. A parameter generation module accesses the label from the label buffer and generates a speech generation parameter. A parameter buffer receives the parameter from the parameter generation module. An audio generation module receives the text input, the label, and/or the parameter and generates a plurality of audio samples, A scheduler monitors and schedules the text and label module, the parameter generation module, and/or the audio generation module. The parameter generation module is further configured to initialize a voice identifier with a Voice Style Sheet (VSS) parameter, receive an input indicating a modification to the VSS parameter, and modify the VSS parameter according to the modification.

Abstract: In general, embodiments relate to a method for managing a technical support session, comprising: determining a technical support issue (TSI) for a technical support session; identifying a question path graph (QPG) associated with the TSI; and displaying at least a portion of the QPG to a technical support person (TSP) during the technical support session.

Abstract: Devices, computer-readable media, and methods for changing the state of a network-connected device in response to at least one facial gesture of a user are disclosed. For example, a processing system including at least one processor captures images of a face of a user, detects at least one facial gesture of the user from the images, determines an intention to change a state of a network-connected device from the at least one facial gesture, generates a command for the network-connected device in accordance with the intention, and outputs the command to cause the state of the network-connected device to change.

Abstract: The present disclosure relates to a relay device of a wireless network, said wireless network comprising a plurality of network nodes mutually connected by wireless links. The relay device is configured to receive a voice command by a microphone of a source node, determine a recipient voice assistant for processing the voice command, and transmit, towards the recipient voice assistant, an output signal comprising the voice command. The present disclosure relates also to a voice assistant and to a wireless network, and to methods for processing voice commands by a relay device and a voice assistant.

Abstract: Implementations relate to receiving natural language input that requests an automated assistant to provide information and processing the natural language input to identify the requested information and to identify one or more predicted actions. Those implementations further cause a computing device, at which the natural language input is received, to render the requested information and the one or more predicted actions in response to the natural language input. Yet further, those implementations, in response to the user confirming a rendered predicted action, cause the automated assistant to initialize the predicted action.

Abstract: A computing system helps a user in an extended reality (XR) learning experience achieve mastery through personalized, programmable and conversational coaching. One aspect is that the XR learning experience may consist of a plurality of tasks associated with the user. A second aspect is that the XR learning experience can define different types of conversational interventions triggered by the computing system at various times. A third aspect is that some tasks or interventions can make use of a conversational assistant. A fourth aspect is that as the user is going through the XR learning experience, the system determines which, if any, interventions can be triggered based on the user's state.

Abstract: Systems, methods, and devices for recognizing a user are disclosed. A speech-controlled device captures a spoken utterance, and sends audio data corresponding thereto to a server. The server determines content sources storing or having access to content responsive to the spoken utterance. The server also determines multiple users associated with a profile of the speech-controlled device. Using the audio data, the server may determine user recognition data with respect to each user indicated in the speech-controlled device's profile. The server may also receive user recognition confidence threshold data from each of the content sources. The server may determine user recognition data associated that satisfies (i.e., meets or exceeds) a most stringent (i.e., highest) of the user recognition confidence threshold data. Thereafter, the server may send data indicating a user associated with the user recognition data to all of the content sources.

Abstract: A system and method for blocking normal media content signals, such as radio program signals emitted on a speaker and substituting alternative content for blocked signals includes a voice control module operable to receive a blocking command via a microphone. Receiving a blocking command results in the normal content being blocked and predetermined alternative content is played for either a user specified time or a predetermined time. Control over the radio or other media device is completely oral via speech recognition technology. The system may include a predetermined time delay before alternative content is played. The system may include a voice activated survey module (“VAS”) enabling a user to leave comments regarding radio commercial content. Comments are tracked in real time and at finite locations within the content.

Abstract: A process of a voice control method with a cloud server and a terminal device. The voice control method includes: a terminal device receiving voice information; the terminal device querying a control instruction corresponding to the voice information from a local voice database; when the control instruction corresponding to the voice information is not queried in the local voice database, the terminal device uploading the voice information to a cloud server; the cloud server parsing the control instruction corresponding to the voice information; when the control instruction corresponding to the voice information is parsed, the cloud server sending the control instruction to the terminal device; and the terminal device receiving the control instruction, and performing a corresponding operation on the basis of control instruction.

Abstract: Systems and methods for a computerized interactive voice companion include functionality that receives audio of a user's voice as the user is speaking; detects a tone and/or other relevant aspects associated with the content of the user's voice based on the audio of the user's voice as the user is speaking and determines, as the user is speaking, a response to the user speaking based on the detected tone and/or other relevant aspects associated with the content of the user's voice of the user's voice. The computerized interactive voice companion system, then orally or visually provides the response to the user automatically in real-time as a reply to the user speaking. The system may then continue the conversation based on continuing to detect the mood of the user as they speak and basing responses on this, as well as other recent user behavior detected to be relevant to the conversation.

Abstract: A faucet is provided that electronically controls the flow volume and temperature of water being dispensed. The faucet illustratively includes a faucet body and a faucet handle. In some embodiments, the faucet may include a faucet body and be voice controlled. The faucet illustratively includes an inertial motion unit sensor mounted in the faucet handle to sense spatial orientation of the faucet handle. The faucet illustratively includes an electronic flow control system to adjust flow volume and temperature of water being dispensed. The faucet illustratively includes a controller configured to receive signals from the inertial motion unit sensor and control the electronic flow control system to adjust flow volume and temperature of water being dispensed based upon the position of the faucet handle.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. For example, a first speech input directed to a digital assistant is received from a user. A first response is provided based on the first speech input. A session window is initiated, wherein the session window is associated with a variable speech threshold. A second speech input is received during the session window. In accordance with a determination that the second speech input includes speech directed to the digital assistant, a duration associated with the session window is increased. In accordance with a determination that the variable speech threshold does not exceed a predetermined speech threshold, the session window is ended.

Abstract: A speech recognition system includes: a speech processor configured to identify an intention of a user included in an utterance of the user; a controller configured to identify whether a function corresponding to the intention of the utterance is performable, and if the function corresponding to the intention of the utterance is not performable, generate spoken text for requesting an other speech recognition system to perform the function corresponding to the intention of the user; and an utterance generator configured to convert the spoken text into a speech signal of an inaudible frequency band.

Abstract: A method for combining hotwords in a single utterance receives, at a first assistant-enabled device (AED), audio data corresponding to an utterance directed toward the first AED and a second AED among two or more AEDs where the audio data includes a query specifying an operation to perform. The method also detects, using a hotword detector, a first hotword assigned to the first AED that is different than a second hotword assigned to the second AED In response to detecting the first hotword, the method initiates processing on the audio data to determine that the audio data includes a term preceding the query that at least partially matches the second hotword assigned. Based on the at least partial match, the method executes a collaboration routine to cause the first AED and the second AED to collaborate with one another to fulfill the query.

Abstract: An artificial intelligence (AI) system for guiding a user interaction in a phone call or chat session. The system includes a computer running an AI algorithm, such as a machine learning algorithm, which is trained to recognize patterns in user interaction dialog which lead to satisfactory outcomes for the user. The system may operate in a completely autonomous mode, or the system connect a human agent in the loop. The algorithm adaptively guides the dialog to achieve a favorable outcome based on the current status of the dialog—including identifying a next question to ask, information to provide, or an action to take. The algorithm is trained via supervised learning using real dialog transcriptions from past user interactions which have been supplemented with decision points and outcomes. After deployment, update training may be performed on the algorithm using data captured by the system after the user interactions.

Abstract: A method for determining potentially undesirable voices, in embodiments, includes: receiving audio recordings comprising voices associated with undesirable activity, and determining audio components of each of the audio recordings. The method may further comprise generating a multi-dimensional vector of the audio components for each of the plurality of audio recordings, and comparing audio components between the multi-dimensional vectors to determine clusters of multi-dimensional vectors, each cluster comprising two or more of the multi-dimensional vectors of audio components, wherein each cluster corresponds to a blacklisted voice. The method may further comprise receiving an audio recording or audio stream, and determining whether the audio recording or audio stream is associated with a voice associated with undesirable activity based on a comparison to the clusters.

Abstract: Systems, methods, and apparatus for using a multimodal response in the dynamic generation of client device output that is tailored to a current modality of a client device is disclosed herein. Multimodal client devices can engage in a variety of interactions across the multimodal spectrum including voice only interactions, voice forward interactions, multimodal interactions, visual forward interactions, visual only interactions etc. A multimodal response can include a core message to be rendered for all interaction types as well as one or more modality dependent components to provide a user with additional information.

Abstract: Embodiments are disclosed for providing an interface with a personalized virtual personal assistant (VPA) via a computing system. The example method comprises assigning a plurality of virtual personal assistant (VPA) instances to a plurality of users, each VPA instance of the plurality of VPA instances operating concurrently. For example, assigning the plurality of VPA instances to the plurality of users may include retrieving a personalized VPA configuration for each user of the plurality of users based on a plurality of audio samples, each of the plurality of audio samples corresponding to a user of the plurality of users.

Abstract: Systems and methods of invoking functions of agents via digital assistant applications are provided. Each action-inventory can have an address template for an action by an agent. The address template can include a portion having an input variable used to execute the action. A data processing system can parse an input audio signal from a client device to identify a request and a parameter to be executed by the agent. The data processing system can select an action-inventory for the action corresponding to the request. The data processing system can generate, using the address template, an address. The address can include a substring having the parameter used to control execution of the action. The data processing system can direct an action data structure including the address to the agent to cause the agent to execute the action and to provide output for presentation.

Abstract: Disclosed are an electronic device, a system, and a controlling method thereof. The controlling method includes: receiving an input utterance, determining whether domain information and intent information are able to be extracted by analyzing the input utterance, based on at least one of the domain information and the intent information not being extracted, broadcasting a signal requesting previous utterance related information to one or more external devices connected to a same network as the electronic device, receiving the previous utterance related information from the at least one external device, extracting the domain information and the intent information based on the received previous utterance related information and the input utterance, and obtaining and outputting a response result based on the extracted domain information and intent information.

Abstract: An artificial intelligence (AI) system for guiding a user interaction in a phone call or chat session. The system includes a computer running an AI algorithm, such as a machine learning algorithm, which is trained to recognize patterns in user interaction dialog which lead to satisfactory outcomes for the user. The system may operate in a completely autonomous mode, or the system connect a human agent in the loop. The algorithm adaptively guides the dialog to achieve a favorable outcome based on the current status of the dialog—including identifying a next question to ask, information to provide, or an action to take. The algorithm is trained via supervised learning using real dialog transcriptions from past user interactions which have been supplemented with decision points and outcomes. After deployment, update training may be performed on the algorithm using data captured by the system after the user interactions.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of customized digital documents. A server tokenizes and encodes historical user interactions and historical digital documents into multidimensional vectors. The server trains an interaction classification model using the multidimensional vectors as input to generate a classification for an input user interaction, and trains a language generation model using the multidimensional vectors as input to generate a customized digital document based upon an input user interaction. The server receives a new user interaction and encodes the new user interaction into a new multidimensional vector. The server executes the trained interaction classification model using the new vector as input to generate a digital document classification. The server executes the trained language generation model using the new vector and the classification as input to generate a customized digital document.

Abstract: A question answering system includes: a first encoder module configured to receive a question, the question including a first plurality of words, and encode the question into a first vector representation; a second encoder module configured to encode a document into a second vector representation, the document including a second plurality of words; a first reading module configured to generate a third vector representation based on the first and second vector representations; a first reformulation module configured to generate a first reformulated vector representation based on the first vector representation; a second reading module configured to generate a fifth vector representation based on the second vector representation and the first reformulated vector representation; a second reformulation module configured to generate a second reformulated vector representation based on first reformulated vector representation; and an answer module configured to determine an answer to the question based on the secon

Abstract: This disclosure proposes systems and methods for speech processing and sharing permitted entity information across speech processing systems. A first system can receive first audio data representing a first utterance. The first system can receive a first dialog identifier associated with a previous utterance. The first system can determine that the first audio data references a first entity. In some cases, the first system may not be able to resolve the first entity based on information in the first audio data. The first system can send, to a second system different from the first system, a first request for information about the first entity. The first request includes the first dialog identifier. The first system can receive first data responsive to the first request from the second system. The first system can process the first data and the first audio data to determine second data responsive to the first utterance, and output a first response representing the second data.

Abstract: System and method for providing presence of modifications in user dictation are disclosed. Exemplary implementations may: obtain primary audio information representing sound, including speech from a recording user, captured by a client computing platform; perform speech recognition on the primary audio information to generate a textual transcript; effectuate presentation of the transcript to the recording user; receive user input from the recording user; alter, based on the received user input from the recording user, a portion of the transcript to generate an altered transcript; effectuate presentation of the altered transcript in conjunction with audio playback of at least some of the primary audio information in a reviewing interface on a client computing platform; receive user input from the reviewing user; alter, based on the received user input from the reviewing user, portions of the altered transcript to generate a reviewed transcript; and store the reviewed transcript in electronic storage.

Abstract: Systems and methods can include a provider institution accounts database structured to retrievably store data corresponding to a plurality of entities including a primary entity related to a plurality of secondary entities. The data for each of the plurality of entities may include values for a plurality of fields associated with the respective entity. A data management circuit may be configured to detect that one or more fields corresponding to at least one of the secondary entities has a value which is to be updated. The data management circuit may generate a first user interface that causes the user to confirm authorization to provide the value for the one or more fields, and a second user interface including a field for receiving the value. The data management circuit may receive the value, and update the data corresponding to the at least one secondary entity in the provider institution accounts database.

Abstract: Provided are a server for providing a response message, based on a voice input of a user, and an operation method of the server. Provided are a server that recognizes health state information of a user, based on a voice input from the user, analyzes pre-stored health data, generates a response message, based on the analyzed health data, and outputs the generated response message, and an operation method of the server. Provided are a server that recognizes event information of a user from a voice input from the user, generates a response message, based on information about the type and frequency of a recognized event, and provides the generated response message, and an operation method of the server.

Abstract: Systems and methods are disclosed for managing a generative artificial intelligence (AI) model. Managing the generative AI model may include training or tuning the generative AI model before use or managing the operation of the generative AI model during use. Training or tuning a generative AI model typically requires manual review of outputs from the model based on the queries provided to the model to reduce hallucinations generated by the generative AI model. Once the model is in use, though, hallucinations still occur. Use of a confidence (whose generation is described herein) to train or tune the generative AI model and/or manage operation of the model reduces hallucinations, and thus improves performance, of the generative AI model.

Abstract: Systems, methods, and computer-readable media are disclosed for processing input data to determine an entity such as a product, service, user profile, etc. referenced in or otherwise relevant to a semantic context of the input data. Information related to the entity may be provided as an information package (e.g., a card) that is shareable as part of an electronic message. The card may include a representation of a network resource identifier that identifies a network resource, a network location of the network resource, and an access mechanism for accessing a representation (e.g. a product detail page) of the network resource. The network resource identifier may include one or more tags or tokens that identify an electronic messaging application provider and/or a user such as a sender or recipient of an electronic message that includes the card so as to enable compensating the provider and/or the user for a purchase of a product or service to which the card relates.

Abstract: Systems for providing network-based communication services are provided, such systems comprising a platform configured to facilitate interaction between users requesting interpretation services and individuals capable of fulfilling such requests. Both the content submitted through the system for interpretation and the resulting interpretation may be prerecorded, which facilitates the accuracy of the end-product. Methods for facilitating communication services over a network are also provided, such methods comprising the steps of receiving a request for interpretation, receiving acceptance of the request from an interpreter, receiving a response that corresponds with an interpretation of the content, and making the response available to one or more users via a server.

Abstract: In a method for improving speech analysis between devices, a processor receives a speech input comprising audio from a speech recognition platform. A processor segments the speech input into input vectors. A processor maps the input vectors to a profile. A processor calculates affinity coefficients between each input vector and the profile. A processor aggregates the input vectors and affinity coefficients in a user profile. A processor implements the user profile in a speech recognition program.

Abstract: The dialogue system includes a keyword acquisition unit configured to acquire an input key group containing one or a plurality of input keywords on the basis of an input of a character string, a category generation unit configured to classify the resulting sentence candidates into a plurality of categories on the basis of a comparison between the input key group acquired by the keyword acquisition unit and the storage key group contained in an FAQ database, an intra-category ranking determination unit configured to determine a priority ranking of the resulting sentence candidates within each of the categories, and a presentation unit configured to select a resulting sentence candidate of a highest priority ranking determined by the intra-category ranking determination unit from within a category of a highest priority ranking determined in advance, and present a response for prompting a user to make an additional input.

Abstract: In an approach to improve chatbot workspaces by updating chatbot workspaces through documentation updating and chatbot skill updating. Embodiments determine a chatbot knowledge base contains a set of updated information and updates a chatbot dialog decision tree based on one or more identified new topics in a set of updated information using natural language processing techniques to determine a set of intents, a set of entities, and a set of keywords. Further, embodiments identify a starting decision for traversing the chatbot dialogue decision tree based on the updated set of entities and the updated set of keywords. Additionally, embodiments interact, via a user interface, with an end user according to one or more interactions traversing the chatbot dialogue decision tree for a response.

Abstract: Methods of authenticating a user or speaker are provided. These methods include obtaining an input speech signal and user credentials identifying the user or speaker. The input speech signal includes a single-channel signal or a multi-channel speech signal. The methods further include extracting a speech voiceprint from the input speech signal, and retrieving a reference voiceprint associated to the user credentials. The methods still further include determining a voiceprint correspondence between the speech voiceprint and the reference voiceprint, and authenticating the user or speaker depending on said voiceprint correspondence. The methods yet further include updating the reference voiceprint depending on the speech voiceprint corresponding to the authenticated user or speaker. Computer programs, systems and computing systems are also provided which are suitable for performing said methods of authenticating a user or speaker.

Abstract: Systems and methods are described herein for alerting a user that the user will be unable to view a broadcast program based on an estimated time of arrival of the user to a media consumption device, and responsively providing the user with an option to record the broadcast program. These systems and methods are performed at least by identifying a plurality of broadcast programs that are indicated on a profile of a user, receiving an estimated time of arrival of the user to a location of a media consumption device, responsively determining whether the user will be unable to view a broadcast program of the plurality of broadcast programs, responsively providing the user with an option to record the broadcast program, and responsively causing the broadcast program to be recorded.

Abstract: A method for processing multi-modal input includes receiving multiple signal inputs, each signal input having a corresponding input mode. Each signal input is processed in a series of mode-specific processing stages. Each successive mode-specific stage is associated with a successively longer scale of analysis of the signal input. A fused output is generated based on the output of a series of fused processing stages. Each successive fused processing stage is associated with a successively longer scale of analysis of the signal input. Multiple fused processing stages receive inputs from corresponding mode-specific processing stages, so that the fused output depends on the multiple of signal inputs.

Abstract: A computer implemented method, system and program product is provided for linguistic alignment in specific user targeted messaging. In one embodiment, new and previously existing data about a specific user is analyzed and personality insights are determined. Location of the user is also determined. Using this location and collected data and personality insights, a multilayered set of linguistic preferences is determined for the specific user. This set is used to customize a message for the specific user based on the linguistic set and ultimately a message is sent to the specific user using a selected messaging channel.

Abstract: Devices and techniques are generally described for machine learning personalization as a service for speech processing applications. In various examples, a first request for machine learning prediction for a first speech processing skill. First skill data schema data may be received that describes content of the first speech processing skill. A first machine learning model for the first speech processing skill may be determined. A first feature definition describing a first aspect of the content may be determined. A second feature definition describing user profile data may be determined. A prediction request may be received from the first speech processing skill. First feature data may be generated according to the first feature definition and second feature data may be generated according to the second feature definition based at least in part on the prediction request.

Abstract: In some examples, an electronic device comprises an image sensor to detect a user action, an audio input device to receive an audio signal, and a processor coupled to the audio input device and the image sensor. The processor is to determine that the audio signal includes private speech based on the user action, remove the private speech from the audio signal to produce a filtered audio signal, and transmit the filtered audio signal.

Abstract: A method of twinning a primary wireless communication device with an in-vehicle wireless communication device. The method comprises inputting a plurality of phone numbers into the in-vehicle wireless communication device that comprises an eSIM storing an eSIM profile provisioned for wireless communication service in a wireless communication network, wherein each phone number is associated with a primary wireless communication device of a different user; sending a first bundle of twinning credentials by the in-vehicle wireless communication device to the wireless communication network, wherein the first bundle of twinning credentials comprises a VIN, an ICCID identifying the eSIM, an EID identifying the eSIM profile, and a first phone number of the plurality of phone numbers input into the in-vehicle communication device associated with a primary wireless communication device of a first user; and providing wireless communication service by the in-vehicle communication device based on the first phone number.