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公开(公告)号：US11288309B2
公开(公告)日：2022-03-29
申请号：US15951219
申请日：2018-04-12
Inventor： Bilei Zhu , Fangmai Zheng , Xingming Jin , Ke Li , Yongjian Wu , Feiyue Huang
IPC: G06F16/632 , G06F16/61 , G06F16/683 , G06F16/00 , G06F3/16 , G10L25/90
Abstract: A melody information processing method is described. A piece of Musical Instrument Digital Interface (MIDI) data corresponding to a song is received, a song identifier of the song is obtained, first melody information is generated according to the MIDI data, and the first melody information is stored in association with the song identifier in a melody database. Moreover, a user unaccompanied-singing audio data set that is uploaded from a user terminal is received, second melody information corresponding to the song identifier is extracted according to the user unaccompanied-singing audio data set, and the second melody information is stored in association with the song identifier in the melody database.
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公开(公告)号：US11087476B2
公开(公告)日：2021-08-10
申请号：US16890087
申请日：2020-06-02
Inventor： Changwei He , Chengjie Wang , Jilin Li , Yabiao Wang , Yandan Zhao , Yanhao Ge , Hui Ni , Yichao Xiong , Zhenye Gan , Yongjian Wu , Feiyue Huang
Abstract: A trajectory tracking method is provided for a computer device. The method includes performing motion tracking on head images in a plurality of video frames, to obtain motion trajectories corresponding to the head images; acquiring face images corresponding to the head images in the video frames, to obtain face image sets corresponding to the head images; determining from the face image sets corresponding to the head images, at least two face image sets having same face images; and combining motion trajectories corresponding to the at least two face image sets having same face images, to obtain a final motion trajectory of trajectory tracking.
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公开(公告)号：US10706263B2
公开(公告)日：2020-07-07
申请号：US16409341
申请日：2019-05-10
Inventor： Chengjie Wang , Jilin Li , Feiyue Huang , Kekai Sheng , Weiming Dong
IPC: G06K9/00
Abstract: Disclosed are an evaluation method and an evaluation device for a facial key point positioning result. In some embodiments, the evaluation method includes: acquiring a facial image and one or more positioning result coordinates of a key point of the facial image; performing a normalization process on the positioning result coordinate and an average facial model to obtain a normalized facial image; and extracting a facial feature value of the normalized facial image and calculating an evaluation result based on the facial feature value and a weight vector.
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公开(公告)号：US10699699B2
公开(公告)日：2020-06-30
申请号：US15993332
申请日：2018-05-30
Inventor： Fuzhang Wu , Binghua Qian , Wei Li , Ke Li , Yongjian Wu , Feiyue Huang
Abstract: The embodiments of the present disclosure disclose a method for constructing a speech decoding network in digital speech recognition. The method comprises acquiring training data obtained by digital speech recording, the training data comprising a plurality of speech segments, and each speech segment comprising a plurality of digital speeches; performing acoustic feature extraction on the training data to obtain a feature sequence corresponding to each speech segment; performing progressive training starting from a mono-phoneme acoustic model to obtain an acoustic model; acquiring a language model, and constructing a speech decoding network by the language model and the acoustic model obtained by training.
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公开(公告)号：US10650830B2
公开(公告)日：2020-05-12
申请号：US15954416
申请日：2018-04-16
Inventor： Wei Li , Binghua Qian , Xingming Jin , Ke Li , Fuzhang Wu , Yongjian Wu , Feiyue Huang
Abstract: Processing circuitry of an information processing apparatus obtains a set of identity vectors that are calculated according to voice samples from speakers. The identity vectors are classified into speaker classes respectively corresponding to the speakers. The processing circuitry selects, from the identity vectors, first subsets of interclass neighboring identity vectors respectively corresponding to the identity vectors and second subsets of intraclass neighboring identity vectors respectively corresponding to the identity vectors. The processing circuitry determines an interclass difference based on the first subsets of interclass neighboring identity vectors and the corresponding identity vectors; and determines an intraclass difference based on the second subsets of intraclass neighboring identify vectors and the corresponding identity vectors. Further, the processing circuitry determines a set of basis vectors to maximize a projection of the interclass difference on the basis vectors and to minimize a projection of the intraclass difference on the basis vectors.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20190221202A1
公开(公告)日：2019-07-18
申请号：US16365458
申请日：2019-03-26
Inventor： Wei Li , Hangyu Yan , Ke Li , Yongjian Wu , Feiyue Huang
IPC: G10L13/10 , G10L13/047 , G06F17/16 , G06N7/00
Abstract: A statistical parameter modeling method is performed by a server. After obtaining model training data, the model training data including a text feature sequence and a corresponding original speech sample sequence, the server inputs an original vector matrix formed by matching a text feature sample point in the text feature sample sequence with a speech sample point in the original speech sample sequence into a statistical parameter model for training and then performs non-linear mapping calculation on the original vector matrix in a hidden layer, to output a corresponding prediction speech sample point. The server then obtains a model parameter of the statistical parameter model according to the prediction speech sample point and a corresponding original speech sample point by using a smallest difference principle, to obtain a corresponding target statistical parameter model.
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7.发明申请公开(公告)号：US20190115031A1
公开(公告)日：2019-04-18
申请号：US16213421
申请日：2018-12-07
Inventor： Wei Li , Binghua Qian , Xingming Jin , Ke Li , Fuzhang Wu , Yongjian Wu , Feiyue Huang
Abstract: An identity vector generation method is provided. The method includes obtaining to-be-processed speech data. Corresponding acoustic features are extracted from the to-be-processed speech data. A posterior probability that each of the acoustic features belongs to each Gaussian distribution component in a speaker background model is calculated to obtain a statistic. The statistic is mapped to a statistic space to obtain a reference statistic, the statistic space built according to a statistic corresponding to a speech sample exceeding a threshold speech duration. A corrected statistic is determined according to the calculated statistic and the reference statistic; and an identity vector is generated according to the corrected statistic.
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公开(公告)号：US12131580B2
公开(公告)日：2024-10-29
申请号：US17733968
申请日：2022-04-29
Inventor： Jian Li , Bin Zhang , Yabiao Wang , Jinlong Peng , Chengjie Wang , Jilin Li , Feiyue Huang , Yongjian Wu
CPC classification number: G06V40/164 , G06N3/08 , G06V10/806 , G06V40/168
Abstract: A face detection method includes: acquiring a target image; invoking a face detection network, and processing the target image by using a feature extraction structure of the face detection network, to obtain original feature maps corresponding to the target image; the original feature maps having different resolutions; processing the original feature maps by using a feature enhancement structure of the face detection network, to obtain an enhanced feature map corresponding to each original feature map; the feature enhancement structure being obtained by searching a search space, and the search space used for searching the feature enhancement structure being determined based on a detection objective of the face detection network and a processing object of the feature enhancement structure; and processing the enhanced feature map by using a detection structure of the face detection network, to obtain a face detection result of the target image.
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9.发明授权公开(公告)号：US11289069B2
公开(公告)日：2022-03-29
申请号：US16365458
申请日：2019-03-26
Inventor： Wei Li , Hangyu Yan , Ke Li , Yongjian Wu , Feiyue Huang
IPC: G10L13/10 , G10L13/08 , G06N7/00 , G06F17/16 , G10L13/047
Abstract: A statistical parameter modeling method is performed by a server. After obtaining model training data, the model training data including a text feature sequence and a corresponding original speech sample sequence, the server inputs an original vector matrix formed by matching a text feature sample point in the text feature sample sequence with a speech sample point in the original speech sample sequence into a statistical parameter model for training and then performs non-linear mapping calculation on the original vector matrix in a hidden layer, to output a corresponding prediction speech sample point. The server then obtains a model parameter of the statistical parameter model according to the prediction speech sample point and a corresponding original speech sample point by using a smallest difference principle, to obtain a corresponding target statistical parameter model.
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公开(公告)号：US11275932B2
公开(公告)日：2022-03-15
申请号：US16938858
申请日：2020-07-24
Inventor： Siqian Yang , Jilin Li , Yongjian Wu , Yichao Yan , Keke He , Yanhao Ge , Feiyue Huang , Chengjie Wang
Abstract: This application discloses a human attribute recognition method performed at a computing device. The method includes: determining a human body region image in a surveillance image; inputting the human body region image into a multi-attribute convolutional neural network model, to obtain, for each of a plurality of human attributes in the human body region image, a probability that the human attribute corresponds to a respective predefined attribute value, the multi-attribute convolutional neural network model being obtained by performing multi-attribute recognition and training on a set of pre-obtained training images by using a multi-attribute convolutional neural network; determining, for each of the plurality of human attributes in the human body region image, the attribute value of the human attribute based on the corresponding probability; and displaying the attribute values of the plurality of human attributes next to the human body region image.
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