Abstract: A microscope control method for operating a microscope, includes: capturing an item of acoustic, graphically represented and/or electronically coded voice information; comparing the voice information with stored reference commands and determining a voice command on the basis of a predetermined degree of correspondence between at least one section of the voice information and a reference command; selecting that reference command to which the voice command corresponds at least to a predetermined degree; generating at least one control command suitable for operating the microscope, wherein the control command is either an invariable control command assigned to the selected reference command or the control command is generated on the basis of a rule assigned to the reference command for forming a generated control command, and controlling the microscope by means of the assigned or generated control command. Also, a microscope is designed to carry out the microscope control method.

Abstract: Disclosed are a method and an apparatus for high frequency decoding for bandwidth extension. The method for high frequency decoding for bandwidth extension comprises the steps of: decoding an excitation class; transforming a decoded low frequency spectrum on the basis of the excitation class; and generating a high frequency excitation spectrum on the basis of the transformed low frequency spectrum. The method and apparatus for high frequency decoding for bandwidth extension according to an embodiment can transform a restored low frequency spectrum and generate a high frequency excitation spectrum, thereby improving the restored sound quality without an excessive increase in complexity.

Abstract: Many portable playback devices cannot decode and playback encoded audio content having wide bandwidth and wide dynamic range with consistent loudness and intelligibility unless the encoded audio content has been prepared specially for these devices. This problem can be overcome by including with the encoded content some metadata that specifies a suitable dynamic range compression profile by either absolute values or differential values relative to another known compression profile. A playback device may also adaptively apply gain and limiting to the playback audio. Implementations in encoders, in transcoders and in decoders are disclosed.

Abstract: Embodiments relate to an audio processing unit that includes a buffer, bitstream payload deformatter, and a decoding subsystem. The buffer stores at least one block of an encoded audio bitstream. The block includes a fill element that begins with an identifier followed by fill data. The fill data includes at least one flag identifying whether enhanced spectral band replication (eSBR) processing is to be performed on audio content of the block. A corresponding method for decoding an encoded audio bitstream is also provided.

Abstract: Systems and methods for determining identifying semantic entities in audio signals are provided. A method can include obtaining, by a computing device comprising one or more processors and one or more memory devices, an audio signal concurrently heard by a user. The method can further include analyzing, by a machine-learned model stored on the computing device, at least a portion of the audio signal in a background of the computing device to determine one or more semantic entities. The method can further include displaying the one or more semantic entities on a display screen of the computing device.

Abstract: Embodiments include computer-implemented methods and systems for detecting undesirable and potentially harmful online behavior. The embodiments described and claimed could also be applied to detecting any other type of online behavior to be detected, but the descriptions focuses on detecting online violence. More particularly, the embodiments disclosed relate to detecting online violence using symbolic methods of natural language processing (NLP) that utilize and govern the usage of: 1) syntactic parser for analyzing grammatical context of the input text data, 2) unsupervised learning methods for improving selected aspects of the system and adjusting the system to new data sources and guidelines, and 3) statistical classifiers for resolving specific well-defined sub-tasks, in which statistical approaches surpass the symbolic methods.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for selecting a digital assistant from among multiple digital assistants. An embodiment operates by receiving a voice input containing a trigger word at a first voice adapter associated with a digital assistant that generates a first confidence score for the trigger word. The embodiment further receives the voice input at a second voice adapter that generates a second confidence score for the trigger word. The embodiment determines the first confidence score is higher than the second confidence score. The embodiment selects the digital assistant based on the determining.

Abstract: A system is provided for determining when supplemental content unresponsive to a user input is to be presented during a user interaction. The system determines an action, performance of which, may trigger output of supplemental content. The system may determine when, during a user interaction corresponding to performance of the action, supplemental content may be presented. The system may use constraint data indicating a device type via which the content may be presented, and a time duration during which the supplemental content may be presented. If the constraint data is satisfied, the system may determine to present the supplemental content.

Abstract: An electronic apparatus for compressing a neural network model may acquire training data pairs based on an original, trained neural network model and train a compressed neural network model compressed from the original, trained neural network model using the acquired training data pairs.

Abstract: Embodiments described herein include a method for insertion of formatted text with speech recognition. One embodiment of the method includes creating a speech recognition command and executing the speech recognition command. Creating the speech recognition command may include receiving a selection by a user to add a plurality of actions to the speech recognition command and receiving a user-defined trigger command for the speech recognition command. In some embodiments, creating the speech recognition command includes receiving a definition of the text grammar, wherein the definition of the text grammar includes at least one command part and at least one command definition and storing the speech recognition command.

Abstract: Understanding emojis in the context of online experiences is described. In at least some embodiments, text input is received and a vector representation of the text input is computed. Based on the vector representation, one or more emojis that correspond to the vector representation of the text input are ascertained and a response is formulated that includes at least one of the one or more emojis. In other embodiments, input from a client machine is received. The input includes at least one emoji. A computed vector representation of the emoji is used to look for vector representations of words or phrases that are close to the computed vector representation of the emoji. At least one of the words or phrases is selected and at least one task is performed using the selected word(s) or phrase(s).

Abstract: In an embodiment of the disclosure, disclosed is an electronic device including a communication module, a microphone, a first and a second wake-up recognition module, a memory, and a processor. The processor is configured to receive a first user utterance through the microphone, recognize the first user utterance based on at least one of the first or the second wake-up recognition module, when the recognized first user utterance includes specified at least one first trigger information, record at least part of the first user utterance by activating the recording function, transmit recorded data to an external device, and receive at least one of second user utterance information, which is predicted to occur at a time after the function of the speech recognition service is activated by the first wake-up recognition module, or at least one response information associated with the second user utterance from the external device.

Abstract: A voice aware audio system and a method for a user wearing a headset to be aware of an outer sound environment while listening to music or any other audio source. An adjustable sound awareness zone gives the user the flexibility to avoid hearing far distant voices. The outer sound can be analyzed in a frequency domain to select an oscillating frequency candidate and in a time domain to determine if the oscillating frequency candidate is the signal of interest. If the signal directed to the outer sound is determined to be a signal of interest the outer sound is mixed with audio from the audio source.

Abstract: Systems and methods include activation of a first voice assistant application to execute a first user dialog session, the first application associated with a first voice keyword and, while the first application is active and executing the first session, reception of second audio signals representing a second voice keyword associated with a second voice assistant application, determination, in response to reception of the second audio signals, that the first application is uninterruptable, wherein the second application remains inactive in response to reception of the second audio signals, reception of a signal from the first application indicating that the first application is interruptable, reception of third audio signals representing the second keyword and, in response to reception of the third audio signals, determination that the first application is interruptable and transmission of an activation signal to the second application to activate the second application and execute a second user dialog session

Abstract: Various embodiments are provided for intelligent selection of time series models by one or more processors in a computing system. Time series data may be received from a user, one or more computing devices, sensors, or a combination thereof. One or more optimal time series models may be selected upon using and/or evaluating one or more recurrent neural networks models that are trained or pre-trained using simulated time series data or historical time series data, or a combination thereof for one or more predictive analytical tasks relating to the received time series data.

Abstract: The invention relates to a method for operating and a method for controlling a dialog system, wherein the dialog system comprises a local dialog unit for detecting dialog inputs and for outputting dialog outputs as well as an external dialog unit having a data connection to the local dialog unit for analyzing detected dialog inputs and determining dialog outputs based thereon. At least one probable future course of dialog consisting of dialog inputs and/or dialog outputs is calculated and transmitted to the local dialog unit by the external dialog unit. Said course of dialog is received and saved by the local dialog unit. The saved course of dialog is called up in the event of an interruption to the data connection between the local dialog unit and the external dialog unit. Dialog inputs are detected and/or dialog outputs are output based on the called-up course of dialog.

Abstract: Technologies are disclosed for disambiguating contact information using relationship data using a virtual assistant. A user interacts with a virtual assistant to obtain and utilize contact information. For example, a virtual assistant may allow users to perform an action that utilizes contact information (e.g., make a call to a contact). The virtual assistant utilizes a contact service to identify candidate contacts that are related to the requesting user. The contact service identifies candidate contacts based on relationship data between the requesting user and the stored contacts. For example, the relationship data may indicate that the requesting user is on the same project or team as another contact, that the requesting user has the same role as another contact, that the requesting user is a manager of another contact, as well as other attributes. In some examples, the contact service limits the number of candidate contacts provided to requesting user.

Abstract: Methods, systems, apparatus, and computer-readable media for providing a voice assistant for to leverage information from sensing devices. In some implementations, one or more computers receive measurement data generated by a sensing device associated with a user. The one or more computers store the measurement data in association with an identifier for the user. The one or more computers obtain text of an utterance of the user detected by a client device associated with the user through a voice interface provided by the client device. The one or more computers access the measurement data associated with the user, and in response to obtaining the text of the utterance, generate a response to the utterance based on the text of the utterance and the stored measurement data. The one or more computers provide response data indicating the generated response.

Abstract: An agent device includes: a plurality of agent function units, in which each of the agent function units provides a service including a voice response to an occupant of a vehicle in response to an utterance of the occupant; and a manager which, when any of the plurality of agent function units is being activated and the predetermined same operation is performed on the plurality of agent function units by the occupant of the vehicle, causes the agent function unit which is being activated to stop.

Abstract: A method for controlling an AI apparatus mounted on home appliance, the method comprising: receiving a sound signal at a predetermined time; removing noises of the received signal and separating the signal from which the noises are removed, into a signal by a user and a device signal; acquiring a result value outputted by an AI model by inputting the separated signal to the AI model using a multi-class separation; and executing a sleep mode of the home appliance and outputting a sleep mode switch notice when the result value is a user sleep, and requesting a feedback from the user when the result value is an unclear signal and updating the AI model using the feedback.