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公开(公告)号:US20230377560A1
公开(公告)日:2023-11-23
申请号:US17747704
申请日:2022-05-18
Applicant: Lemon Inc.
Inventor: Han WANG , Hongyu XIONG , Yiqi FENG , Yuan GAO , Xiangyu ZENG , Rui LI , Qingyi LU , Bin LIU
Abstract: Embodiments of the present disclosure relate to speech tendency classification. According to embodiments of the present disclosure, a method comprises extracting, from a speech segment, voiceprint information and at least one of volume information or speaking rate information; determining, based on the voiceprint information, first probability information indicating respective first probabilities of a plurality of tendency categories into which the speech segment is classified; determining, based on the at least one of the volume information or the speaking rate information, second probability information indicating respective second probabilities of the plurality of tendency categories into which the speech segment is classified; and determining, based at least in part on the first probability information and the second probability information, target probability information for the speech segment, the target probability information indicating respective target probabilities of the plurality of tendency categories into which the speech segment is classified.
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公开(公告)号:US20230334839A1
公开(公告)日:2023-10-19
申请号:US17724140
申请日:2022-04-19
Applicant: Lemon Inc.
Inventor: Xiangyu ZENG , Hongyu XIONG , Yiqi FENG , Han WANG , Yuan GAO , Qingyi LI , Rui LI
CPC classification number: G06V10/806 , G06V30/1448 , G06V10/225 , G10L15/26 , G06V10/40
Abstract: Implementations of the present disclosure relate to methods, devices, and computer program products of extracting a feature for multimedia data that comprises a plurality of medium types. In a method, a first feature is determined for a first medium type in the plurality of medium types by masking a portion in a first medium object with the first medium type. A second feature is determined for a second medium type other than the first medium type in the plurality of medium types. The feature is generated for the multimedia data based on the first and second features. With these implementations, multiple medium types are considered in the feature extraction, and thus the feature may fully reflect various aspects of the multimedia data in an accurate way.
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公开(公告)号:US20230342553A1
公开(公告)日:2023-10-26
申请号:US17727015
申请日:2022-04-22
Applicant: LEMON INC.
Inventor: Hongyu XIONG , Han WANG , Yiqi FENG , Rui LI , Yuan GAO , Xiangyu ZENG , Qingyi LU , Bin LIU
IPC: G06F40/279 , G06F40/30 , G06N3/04
CPC classification number: G06F40/30 , G06F40/279 , G06N3/0454
Abstract: Embodiments of the present disclosure relate to attribute and rating co-extraction. According to embodiments of the present disclosure, a method is proposed. The method comprises: determining, by a first sub-network of a model, a first feature representation based on a first token contained in a text, the first feature representation indicating semantic information of the first token in the text; determining, by a second sub-network of the model, first attribute information associated with the first token based on the first feature representation, the first attribute information indicating a first attribute involved in the text; and determining, by a third sub-network of the model, first rating information associated with the first token based on the first feature representation, the first rating information indicating a rating related to the first attribute.
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公开(公告)号:US20230342544A1
公开(公告)日:2023-10-26
申请号:US17728248
申请日:2022-04-25
Applicant: LEMON INC.
Inventor: Hongyu XIONG , Han WANG , Rui LI , Yiqi FENG , Yuan GAO , Xiangyu ZENG , Qingyi LU , Bin LIU
IPC: G06F40/211 , G06F16/33 , G06F40/30 , G06F40/14
CPC classification number: G06F40/211 , G06F16/3344 , G06F40/30 , G06F40/14
Abstract: Embodiments of the present disclosure relate to semantic parsing for short text. According to embodiments of the present disclosure, a method is proposed. The method comprises: obtaining a set of sentences associated with a short text, each of the set of sentences containing all of words in the short text; determining a set of syntactic features associated with the set of sentences, each of the set of syntactic features indicating at least one of a constituency relation and a dependency relation of the corresponding sentence; and determining a semantic structure of the short text based on the set of syntactic features.
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