Abstract: A voice control device includes a user database, a first image capturing module, a voice command module and a management module. The user database stores first user identification data of a first user account. The first image capturing module captures an environmental image. The voice command module is enabled to receive a voice command for controlling the voice control device. The management module is used to detect whether at least one facial image exists in the environmental image, and detect whether the facial image matches with the first user identification data, and when the facial image matches with the first user identification data, the management module logs in the first user account and enables the voice command module.

Abstract: One or more non-transitory computer readable media contain program instructions that, when executed, cause one or more processors to: receive first raw data including one or more first data points generated by a first object of a plurality of objects associated with one or more buildings; generate first input timeseries according to the one or more data points; access a database of interconnected smart entities, the smart entities including object entities representing each of the plurality of objects and data entities representing stored data, the smart entities being interconnected by relational objects indicating relationships between the smart entities; identify a first object entity representing the first object from a first identifier in the first input timeseries; identify a first data entity from a first relational object indicating a relationship between the first object entity and the first data entity; and store the first input timeseries in the first data entity.

Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed.

Abstract: A method of controlling a terminal is provided. The method includes analyzing a sensed voice when a voice is sensed, recognizing a context based a result of the analysis, and performing a predetermined control operation based on the recognized context.

Abstract: This disclosure describes, in part, context-driven device arbitration techniques to select a speech interface device from multiple speech interface devices to provide a response to a command included in a speech utterance of a user. In some examples, the context-driven arbitration techniques may include executing multiple pipeline instances to analyze audio signals and device metadata received from each of the multiple speech interface devices which detected the speech utterance. A remote speech processing service may execute the multiple pipeline instances and analyze the audio signals and/or metadata, at various stages of the pipeline instances, to determine which speech interface device is to respond to the speech utterance.

Abstract: An artificial intelligence server for setting a language of a robot includes a communication unit and a processor. The communication unit is configured to communicate with the robot. The processor is configured to receive voice data for a control area from the robot, generate first language distribution information using the received voice data, receive event information for the control area, generate second language distribution information using the received event information, determine at least one major output language for the robot based on the generated first language distribution information and the generated second language distribution information, and transmit a control signal for setting the determined major output language to the robot.

Abstract: A method for natural language interaction includes recording speech provided by a human user. The recorded speech is translated into a machine-readable natural language input relating to an interaction topic. An interaction timer is maintained that tracks a length of time since a last machine-readable natural language input referring to the interaction topic was translated. Based on a current value of the interaction timer being greater than an interaction engagement threshold, a message relating to the interaction topic is delivered with a first natural language phrasing that includes an interaction topic reminder. Based on the current value of the interaction timer being less than the interaction engagement threshold, the message relating to the interaction topic is delivered with a second natural language phrasing that lacks the interaction topic reminder.

Abstract: An audio decoder for providing a decoded audio information on the basis of an encoded audio information is disclosed. The audio decoder includes a linear-prediction-domain decoder configured to provide a first decoded audio information on the basis of an audio frame encoded in a linear prediction domain, a frequency domain decoder configured to provide a second decoded audio information on the basis of an audio frame encoded in a frequency domain, and a transition processor. The transition processor is configured to obtain a zero-input-response of a linear predictive filtering, wherein an initial state of the linear predictive filtering is defined depending on the first decoded audio information and the second decoded audio information, and modify the second decoded audio information depending on the zero-input-response, to obtain a smooth transition between the first and the modified second decoded audio information.

Abstract: Techniques for extracting clinical entities from clinical documents are provided. In some embodiments, a non-transitory machine-readable medium stores a program. The program receives a clinical document partitioned into a set of sections. Each section in the set of sections includes a plurality of terms. The program further identifies a section in the set of sections. The program also determines a subset of a plurality of entity recognizers based on a classification of the section. Each entity recognizer in the plurality of entity recognizers is configured to identify terms in the section as being associated with a particular type of data. The program further sends the section to the subset of the entity recognizers for processing. The program also generates a clinical statement based on terms identified in the section by the subset of the plurality of entity recognizers.

Abstract: An apparatus estimates, based on an input from a user to an interaction performed during a conversation between the user and the apparatus, an interest degree indicating a degree of interest of the user in a first topic included in the interaction, and estimates, based on the input from the user to the interaction, acceptability of the interaction by the user. The apparatus selects, in accordance with the interest degree and the acceptability, as an operation mode for performing the interaction, one of a first mode of leaving an interaction initiative to the user and a second mode in which the interaction proceeds under an initiative of a system for a specific topic. The apparatus generates interaction data according to the selected operation mode, and causes an output device to output the generated interaction data.

Abstract: Aspects of the present invention disclose a method for preventing adversarial audio attacks through detecting and isolating inconsistencies utilizing beamforming techniques and IoT devices. The method includes one or more processors identifying an audio command received by a listening device. The method further includes determining a source location of the audio command utilizing a sensor array of the listening device. The method further includes determining a location of a user in relation to the listening device based on data of an Internet of Things (IoT) device. The method further includes determining an inconsistency between the determines source location and the determined location of the user based at least in part on data of the sensor array and data of the IoT device.

Abstract: The present disclosure provides a system for predicting a disease state based on speech occurrences. A feature extraction module extracts a plurality of lingual features from a speech record of the speech occurrence. The lingual features are chosen based on a correlation between the lingual features and the disease state in at least a first language and a second language. The lingual features are consistent for transcripts in at least the first language and the second language. A prediction module including a trained classification model generates a prediction of the disease state for speech occurrences in at least the first language and the second language using the lingual features extracted from the speech records.

Abstract: A computer-implemented method includes receiving a message of a pharmacy customer wherein the message includes a text string, and generating a set of one or more intents corresponding to the pharmacy customer by analyzing the text string using a trained machine learning model, wherein each of the one or more intents correspond to a respective desired action pertaining to the pharmacy order. The machine learning model may be a classification model. The method further includes generating at least one response message based on the set of intents corresponding to the pharmacy customer and transmitting the at least one response message to a mobile device associated with the pharmacy customer. The set of one or more intents may be chosen from a list of commonplace pharmacy customer intents.

Abstract: Embodiments of present disclosure relates to a voice assistant device and method for controlling the voice assistant device. The voice assistant device comprising receiver configured to receive at least one voice input from user, when operated in wake-up mode. Intent associated with the at least one voice input from the at least one user. Further, probability of issuance of a subsequent voice input from the at least one user is determined based on at least one of the intent, historic data and one or more contextual factors. An extended wake-up duration of the voice assistant device is estimated, when the probability is greater than a predefined threshold value. Further, duration of the wake-up mode is extended for the extended wake-up duration to receive the subsequent voice input from the at least one user.

Abstract: Example methods, apparatus and articles of manufacture to determine semantic information for audio are disclosed. Example apparatus disclosed herein are to process an audio signal obtained by a media device to determine values of a plurality of features that are characteristic of the audio signal, compare the values of the plurality of features to a first template having corresponding first ranges of the plurality of features to determine a first score, the first template associated with first semantic information, compare the values of the plurality of features to a second template having corresponding second ranges of the plurality of features to determine a second score, the second template associated with second semantic information, and associate the audio signal with at least one of the first semantic information or the second semantic information based on the first score and the second score.

Abstract: Example articles of manufacture and apparatus for producing supplemental information for audio signature data are disclosed herein. An example apparatus includes memory including computer readable instructions. The example apparatus also includes a processor to execute the instructions to at least obtain first audio signature data associated with a first time period of media, obtain first semantic signature data associated with the first time period of the media and second semantic signature data associated with a second time period of the media, and when second audio signature data associated with the second time period of the media is unavailable, identify the media based on the first audio signature data associated with the first time period of media when the second semantic signature data associated with the second time period matches the first semantic signature data associated with the first time period of the media.

Abstract: An electronic device and a control method therefor are provided. The electronic device comprises: a plurality of microphones for receiving audio signals in which voice signals are included; a communicator for receiving state information according to information about a connection with the electronic device; and a processor for determining the noise environment around the electronic device based on one or more of audio amplitude information that is received by the plurality of microphones and that is output by an external device, and state information of the external device, and for processing the voice signal based on the determined noise environment so as to perform voice recognition.

Abstract: A computer-implemented method for generating ground-truth for natural language querying may include providing a knowledge graph as data model, receiving a natural language query from a user and translating the natural language query into a formal data query. The method can also include visualizing the formal data query to the user and receiving a feedback response from the user. The feedback response can include a verified and/or edited formal data query. The method can also include storing the natural language query and the corresponding feedback response as ground-truth pair. Corresponding system and a related computer program product may be provided.

Abstract: An intelligence-driven virtual assistant for automated documentation of new ideas is provided. During a brainstorming session, one or more user participants may discuss and identify one or more ideas. Such ideas may be tracked, catalogued, analyzed, developed, and further expanded upon through use of an intelligence-driven virtual assistant. Such virtual assistant may capture user input data embodying one or more new ideas and intelligently process the same in accordance with creativity tool workflows. Such workflows may further stimulate creativity for capturing ideas, while continuing to document, analyze, and identify further aspects to develop and expand.

Abstract: An apparatus for the control of a medical implant in a mammal body is provided. The apparatus comprises a first and a second part being adapted to be in electrical connection with each other by using said body as a conductor, in which apparatus the first part is adapted for implantation in the mammal body for the control of and communication with the medical implant, the second part is adapted to be worn on the outside of the mammal body in physical contact with said body and adapted to receive control commands from a user and to transmit these commands to the first part. The apparatus is adapted for communication between the first and the second parts and in that the second part is adapted to receive and recognize the control commands from a user transmitted to the first part for the control of said implant, the first part being adapted to convey such signals to the implant.