Abstract: Embodiment systems and methods for presenting a facial expression in a virtual meeting may include detecting a user facial expression of a user based on information received from a sensor of the computing device, determining whether the detected user facial expression is approved for presentation on an avatar in a virtual meeting, generating an avatar exhibiting a facial expression consistent with the detected user facial expression in response to determining that the detected user facial expression is approved for presentation on an avatar in the virtual meeting, generating an avatar exhibiting a facial expression that is approved for presentation in response to determining that the detected user facial expression is not approved for presentation on an avatar in the virtual meeting, and presenting the generated avatar in the virtual meeting.

Abstract: A processor-implemented method for compressing a deep neural network model includes receiving an initial neural network model. The initial neural network is pruned based on a first threshold to generate a pruned network and a set of pruned weights. A quantization process is applied to the pruned network to produce a pruned and quantized network. A teacher model is generated by incorporating the pruned set of weights with the pruned network. In addition, an initial student model is generated from the quantized and pruned network. The initial student model is trained using the teacher model to output a trained student model.

Abstract: Various embodiments of the disclosure disclose a method and apparatus for processing a voice recognition service in an electronic device. According to various embodiments of the disclosure, an electronic device may include a microphone, a memory, and a processor operatively coupled to the microphone and the memory. The processor may be configured to wake-up on the basis of detection of a wake-up word, process a first task corresponding to a first voice command of a user on the basis of the wake-up, set a wait time during which a follow-up command can be received on the basis of the processing of the first task, detect a second voice command of the user during the wait time, analyze a conversational context on the basis of the first voice command and second voice command, and process a second task on the basis of a result of the analysis. Various embodiments are possible.

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

Abstract: The section-guide graduated ruler for Caesarean section according to the present subject matter includes: a strip-shaped vertical tape having pointed upper and lower ends and having a length corresponding to the distance from the mother's navel to clitoris, and a horizontal tape coupled so as to intersect with the vertical tape, the horizontal tape having a length corresponding to the length of both ilia, thereby guiding a Pfannenstiel incision during Caesarean section.

Abstract: A method for detecting and classifying a domain generation algorithm (DGA) generation domain according to an embodiment of the present disclosure includes entering a domain address expressed as a vector of sequence numbers in a TextCNN, and replacing the vector with a one-hot vector corresponding to sequence number vector elements to express image representation.

Abstract: Various embodiments of the present disclosure relate to an electronic device and a method for executing content by using sight-line information thereof, the electronic device comprising: a display; a sight-line tracking module; a memory storing at least one command; and at least one processor operatively coupled with the display, the sight-line tracking module and the memory.

Abstract: A method for broadcasting contents and a device using the same are provided. The method for broadcasting contents includes displaying a host content window in which a first content is displayed, and displaying an application window in which a second content is displayed, the second content being provided by an application which is executed in the device, where only the first content among the first content and the second content is broadcast to an external device connected to the device.

Abstract: A computer-implemented method of operating an artificial neural network for processing data having a frequency dimension includes receiving an input. The audio input may be separated into one or more subgroups along the frequency dimension. A normalization may be performed on each subgroup. The normalization for a first subgroup the normalization is performed independently of the normalization a second subgroups. An output such as a keyword detection indication, is generated based on the normalized subgroups.

Abstract: A method for generating a personalized model includes receiving one or more personal data samples from a user. A prototype of a personal identity is generated based on the personal data samples. The prototype of the personal identity is trained to reflect personal characteristics of the user. A network graph is generated based on the prototype of the personal identity. One or more channels of a global network are pruned based on the network graph to produce the personalized model.

Abstract: System and method for operating an always-on ASR (automatic speech recognition) system by selecting target keywords and continuously detecting the selected target keywords in voice commands in a mobile device are provided. In the mobile device, a processor is configured to collect keyword candidates, collect usage frequency data for keywords in the keyword candidates, collect situational usage frequency data for the keywords in the keyword candidates, select target keywords from the keyword candidates based on the usage frequency data and the situational usage frequency data, and detect one or more of the target keywords in a voice command using continuous detection of the target keywords.

Abstract: A method performed by an artificial neural network (ANN) includes determining, at a first stage of a multi-stage cross-attention model of the ANN, a first cross-correlation between a first representation of each modality of a number of modalities associated with a sequence of inputs. The method still further includes determining, at each second stage of one or more second stages of the multi-stage cross-attention model, a second cross-correlation between first attended representations of each modality. The method also includes generating a concatenated feature representation associated with a final second stage of the one or more second stages based on the second cross-correlation associated with the final second stage, the first attended representation of each modality, and the first representation of each modality. The method further includes determining a probability distribution between a set of background actions and a set of foreground actions from the concatenated feature representation.

Abstract: Certain aspects of the present disclosure are generally directed to apparatus and techniques for event state detection. One example method generally includes receiving a plurality of sensor signals at a computing device, determining, at the computing device, probabilities of sub-event states based on the plurality of sensor signals using an artificial neural network for each of a plurality of time intervals, and detecting, at the computing device, the event state based on the probabilities of the sub-event states via a state sequence model.

Abstract: A method for broadcasting contents and a device using the same are provided. The method for broadcasting contents includes displaying a host content window in which a first content is displayed, and displaying an application window in which a second content is displayed, the second content being provided by an application which is executed in the device, where only the first content among the first content and the second content is broadcast to an external device connected to the device.

Abstract: Provided are an apparatus and a method, a variety of embodiments of the apparatus comprising a microphone, memory, and a processor functionally connected to the microphone or memory, wherein the processor is configured to: count end-point detection (EPD) time on the basis of a voice input; when the EPD time expires, determine whether the final word of the voice input corresponds to a previously configured word stored in memory; and, if the final word corresponds to the previously configured word, then extend the EPD time and wait for reception of a voice input. Additionally, other embodiments are possible.

Abstract: A device to process an audio signal representing input sound includes a user voice verifier configured to generate a first indication based on whether the audio signal represents a user's voice. The device includes a speaking target detector configured to generate a second indication based on whether the audio signal represents at least one of a command or a question. The device includes an activation signal unit configured to selectively generate an activation signal based on the first indication and the second indication. The device also includes an automatic speech recognition engine configured to be activated, responsive to the activation signal, to process the audio signal.

Abstract: Provided is an apparatus and a method for calculating a viewer rating and, more specifically, to an apparatus and a method for calculating a viewer rating, which process channel change data of a set-top box and can survey a viewer rating per household in real time.

Abstract: A device to perform end-of-utterance detection includes a speaker vector extractor configured to receive a frame of an audio signal and to generate a speaker vector that corresponds to the frame. The device also includes an end-of-utterance detector configured to process the speaker vector and to generate an indicator that indicates whether the frame corresponds to an end of an utterance of a particular speaker.

Abstract: A device includes a screen and one or more processors configured to provide, at the screen, a graphical user interface (GUI) configured to display data associated with multiple devices on the screen. The GUI is also configured to illustrate a label and at least one control input for each device of the multiple devices. The GUI is also configured to provide feedback to a user. The feedback indicates that a verbal command is not recognized with an action to be performed. The GUI is also configured to provide instructions for the user on how to teach the one or more processors which action is to be performed in response to receiving the verbal command.

Abstract: In one embodiment, an electronic device includes an input device configured to provide an input stream, a first processing device, and a second processing device. The first processing device is configured to use a keyword-detection model to determine if the input stream comprises a keyword, wake up the second processing device in response to determining that a segment of the input stream comprises the keyword, and modify the keyword-detection model in response to a training input received from the second processing device. The second processing device is configured to use a first neural network to determine whether the segment of the input stream comprises the keyword and provide the training input to the first processing device in response to determining that the segment of the input stream does not comprise the keyword.