Speech correction system and speech correction method

    公开(公告)号:US11069341B2

    公开(公告)日:2021-07-20

    申请号:US16242325

    申请日:2019-01-08

    Abstract: The speech correction system includes a storage device, an audio receiver and a processing device. The processing device includes a speech recognition engine and a determination module. The storage device is configured to store a database. The audio receiver is configured to receive an audio signal. The speech recognition engine is configured to identify a key speech pattern in the audio signal and generate a candidate vocabulary list and a transcode corresponding to the key speech pattern; wherein the candidate vocabulary list includes a candidate vocabulary corresponding to the key speech pattern and a vocabulary score corresponding to the candidate vocabulary. The determination module is configured to determine whether the vocabulary score is greater than a score threshold. If the vocabulary score is greater than the score threshold, the determination module stores the candidate vocabulary corresponding to the vocabulary score in the database.

    Speech correction system and speech correction method

    公开(公告)号:US10885914B2

    公开(公告)日:2021-01-05

    申请号:US16255943

    申请日:2019-01-24

    Abstract: The speech correction system includes a storage device and a processing device. The storage device stores a first database. The processing device includes an audio receiver, a speech recognition engine, a calculation module, and a determination module. The audio receiver receives multiple voice inputs. The speech recognition engine recognizes the voice inputs, generates multiple candidate vocabularies corresponding to each of the voice inputs, and generates a vocabulary probability corresponding to each of the candidate vocabularies. The calculation module performs a specific operation on the vocabulary probabilities corresponding to the same candidate vocabulary, to generate a plurality of corresponding operation results. The determination module determines whether each of the operation results is greater than a score threshold, and stores at least one output result that is greater than the score threshold to the first database.

    Tooth-position recognition system

    公开(公告)号:US11037317B2

    公开(公告)日:2021-06-15

    申请号:US16707234

    申请日:2019-12-09

    Abstract: A tooth-position recognition system includes an electronic device and a calculation device. The electronic device includes a first camera. The first camera is configured to capture a plurality of tooth images. The calculation device includes a second camera and a processor. The second camera is configured to capture a user image. The processor is configured to receive the tooth images, compare the corresponding position of each pixel in each tooth image to generate a depth map, and input the tooth images, the depth map, and a plurality of first tooth-region identifiers into a tooth deep-learning model. The tooth deep-learning model outputs a plurality of deep-learning probability values that are the same in number as the first tooth-region identifiers. The processor inputs the user image and the plurality of second tooth-region identifiers into a user-image deep-learning model.

    Method and device for improving efficiency of reconstructing three-dimensional model

    公开(公告)号:US10740916B2

    公开(公告)日:2020-08-11

    申请号:US16211354

    申请日:2018-12-06

    Abstract: A method for improving the efficiency of reconstructing a three-dimensional model is provided. The method includes: dividing a series of different Gray code binary illumination patterns into a plurality of groups; converting binary values of Gray code binary illumination patterns in each group to a plurality of sets of two specific values to generate decimal illumination patterns corresponding to the specific values; overlapping the decimal illumination patterns in each group to a grayscale illumination pattern; using a projector to project each grayscale illumination pattern onto an object from a projection direction; using a camera to capture one or more object images of the object; reverting the object images to non-overlapping Gray code binary images corresponding to the object images; and reconstructing the depth of the object according to the non-overlapping Gray code binary images.

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