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公开(公告)号:US11069341B2
公开(公告)日:2021-07-20
申请号:US16242325
申请日:2019-01-08
Applicant: Quanta Computer Inc.
Inventor: Yi-Ling Chen , Chih-Wei Sung , Yu-Cheng Chien , Kuan-Chung Chen
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.
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公开(公告)号:US10885914B2
公开(公告)日:2021-01-05
申请号:US16255943
申请日:2019-01-24
Applicant: Quanta Computer Inc.
Inventor: Kuan-Chung Chen , Chih-Wei Sung , Yu-Cheng Chien , Yi-Ling Chen
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.
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公开(公告)号:US11037317B2
公开(公告)日:2021-06-15
申请号:US16707234
申请日:2019-12-09
Applicant: Quanta Computer Inc.
Inventor: Kai-Ju Cheng , Kuan-Chung Chen , Yu-Cheng Chien , Chung-Sheng Wu , Hao-Ping Lee , Chin-Yuan Ting , Yu-Hsun Chen , Shao-Ang Chen , Jia-Chyi Wang , Chih-Wei Sung
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.
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公开(公告)号:US10740916B2
公开(公告)日:2020-08-11
申请号:US16211354
申请日:2018-12-06
Applicant: Quanta Computer Inc.
Inventor: Kai-Ju Cheng , Yu-Cheng Chien , Yi-Ling Chen , Kuan-Chung Chen
IPC: G06T7/521
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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