Abstract: A high-voltage battery control apparatus includes a plurality of high-voltage battery controllers configured to respectively monitor states of a plurality of high-voltage batteries included in one high-voltage battery pack depending on a predetermined period for monitoring the high-voltage battery pack, wherein the high-voltage battery controllers are configured to transition state of the plurality of high-voltage battery controllers together to an end state when a high-voltage battery controller among the high-voltage battery controllers, which has completed a monitoring operation, first waits until all monitoring operations of the high-voltage battery controllers that have not yet completed monitoring operations are completed and then all the monitoring operations of the high-voltage battery controllers are completed.

Abstract: An infusion flow regulator includes: a main body having an inlet through which fluid is introduced and an outlet through which the fluid is discharged; and a rotary dial rotatably coupled to the main body, with a sealing member interposed therebetween, so as to regulate a flow rate of the fluid, in which the rotary dial includes a regulating flow path having a shape of a recessed groove in cross section with a first width and a first height, and the regulating flow path includes a first region in which the first width is constant and the first height is decreased, and a second region in which both the first width and the first height are decreased. By the aforementioned configuration, the infusion flow regulator for the fluid can accurately regulate the flow rate even in a region where the flow rate of the fluid is very small.

Abstract: An automatic speech recognition (ASR) system that determines a textual representation of a word from a word spoken in a natural language is provided. The ASR system uses an acoustic model, a language model, and a decoder. When the ASR system receives a spoken word, the acoustic model generates word candidates for the spoken word. The language model determines an n-gram score for each word candidate. The n-gram score includes a base score and a bias score. The bias score is based on a logarithmic probability of the word candidate, where the logarithmic probability is derived using a class-based language model where the words are clustered into non-overlapping clusters according to word statistics. The decoder decodes a textual representation of the spoken word from the word candidates and the corresponding n-gram score for each word candidate.

Abstract: The present invention relates to a method for sterilizing a bone graft material, and more specifically, to a method for sterilizing a bone graft material containing sodium carboxymethyl cellulose (CMC) gel without changing its properties.

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.

Abstract: Embodiments described herein provide a query autocompletion (QAC) framework at subword level. Specifically, the QAC framework employs a subword encoder that encodes or converts the sequence of input alphabet letters into a sequence of output subwords. The generated subword candidate sequences from the subword encoder is then for the n-gram language model to perform beam search on. For example, as user queries for search engines are in general short, e.g., ranging from 10 to 30 characters. The n-gram language model at subword level may be used for modeling such short contexts and outperforms the traditional language model in both completion accuracy and runtime speed. Furthermore, key computations are performed prior to the runtime to prepare segmentation candidates in support of the subword encoder to generate subword candidate sequences, thus eliminating significant computational overhead.

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: Embodiments described herein provide a query autocompletion (QAC) framework at subword level. Specifically, the QAC framework employs a subword encoder that encodes or converts the sequence of input alphabet letters into a sequence of output subwords. The generated subword candidate sequences from the subword encoder is then for the n-gram language model to perform beam search on. For example, as user queries for search engines are in general short, e.g., ranging from 10 to 30 characters. The n-gram language model at subword level may be used for modeling such short contexts and outperforms the traditional language model in both completion accuracy and runtime speed. Furthermore, key computations are performed prior to the runtime to prepare segmentation candidates in support of the subword encoder to generate subword candidate sequences, thus eliminating significant computational overhead.

Abstract: Embodiments described herein provide a query autocompletion (QAC) framework at subword level. Specifically, the QAC framework employs a subword encoder that encodes or converts the sequence of input alphabet letters into a sequence of output subwords. The generated subword candidate sequences from the subword encoder is then for the n-gram language model to perform beam search on. For example, as user queries for search engines are in general short, e.g., ranging from 10 to 30 characters. The n-gram language model at subword level may be used for modeling such short contexts and outperforms the traditional language model in both completion accuracy and runtime speed. Furthermore, key computations are performed prior to the runtime to prepare segmentation candidates in support of the subword encoder to generate subword candidate sequences, thus eliminating significant computational overhead.

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: An automatic speech recognition (ASR) system that determines a textual representation of a word from a word spoken in a natural language is provided. The ASR system uses an acoustic model, a language model, and a decoder. When the ASR system receives a spoken word, the acoustic model generates word candidates for the spoken word. The language model determines an n-gram score for each word candidate. The n-gram score includes a base score and a bias score. The bias score is based on a logarithmic probability of the word candidate, where the logarithmic probability is derived using a class-based language model where the words are clustered into non-overlapping clusters according to word statistics. The decoder decodes a textual representation of the spoken word from the word candidates and the corresponding n-gram score for each word candidate.

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.

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: 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: An electronic apparatus and a controlling method thereof. The electronic apparatus includes a display; an outer frame to house the display; an illuminance sensor which detects a sensing value used to determine at least one of illuminance and color temperature of an external light; a memory which stores a background image, which is an image of an area behind the electronic apparatus; and a processor, which generates a content screen comprising an object layer including at least one graphic object and a background image layer including the background image. The display displays the content screen and the processor may correct the background image or provide an image effect based on the sensed values.

Abstract: A display apparatus, including a display configured to display an image, at least one sensor configured to generate sensing data relating to at least one from among a direction and an intensity of external light projected onto the display from an external light source disposed around the display, a memory configured to store background image data relating to a background image of a background area behind the display, and a processor configured to generate a content screen based on the background image data and the sensing data and control the display to display the content screen, wherein the content screen may include at least one graphic object and a shadow corresponding to the at least one graphic object disposed on the background image, and at least one of a position and a shade of the shadow is changed in response to a change in the sensing data.

Abstract: A display apparatus is provided. The display apparatus includes: a display panel; a sensor configured to sense illuminance around the display panel; a communicator configured to perform communication with an external apparatus; and a processor configured to allow a test image having luminance determined on the basis of the sensed illuminance to be displayed on the display panel, receive correction data from the external apparatus photographing the displayed test image through the communicator, and correct luminance of the display panel on the basis of the correction data, wherein the test image is a single color image including a plurality of markers, and the processor allows the test image to be displayed at luminance that becomes relatively high as a level of the sensed illuminance becomes high.

Abstract: An electronic apparatus and a controlling method thereof. The electronic apparatus includes a display; an outer frame to house the display; an illuminance sensor which detects a sensing value used to determine at least one of illuminance and color temperature of an external light; a memory which stores a background image, which is an image of an area behind the electronic apparatus; and a processor, which generates a content screen comprising an object layer including at least one graphic object and a background image layer including the background image. The display displays the content screen and the processor may correct the background image or provide an image effect based on the sensed values.

Abstract: An electronic apparatus and a controlling method thereof. The electronic apparatus includes a display; an outer frame to house the display; an illuminance sensor which detects a sensing value used to determine at least one of illuminance and color temperature of an external light; a memory which stores a background image, which is an image of an area behind the electronic apparatus; and a processor, which generates a content screen comprising an object layer including at least one graphic object and a background image layer including the background image. The display displays the content screen and the processor may correct the background image or provide an image effect based on the sensed values.

Abstract: An electronic apparatus and a controlling method thereof. The electronic apparatus includes a display; an outer frame to house the display; an illuminance sensor which detects a sensing value used to determine at least one of illuminance and color temperature of an external light; a memory which stores a background image, which is an image of an area behind the electronic apparatus; and a processor, which generates a content screen comprising an object layer including at least one graphic object and a background image layer including the background image. The display displays the content screen and the processor may correct the background image or provide an image effect based on the sensed values.