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公开(公告)号：US20220198327A1
公开(公告)日：2022-06-23
申请号：US17348270
申请日：2021-06-15
Inventor： Shuohuan WANG , Chao PANG , Yu SUN
IPC: G06N20/00 , G06N5/02 , G10L25/54 , G10L25/27 , G06F16/9032 , G06F16/907
Abstract: The present disclosure provides a method, apparatus, device and storage medium for training a dialogue understanding model, and relates to technical field of computers, and specifically to the technical field of artificial intelligence such as natural language processing and deep learning. The method for training a dialogue understanding model includes: obtaining dialogue understanding training data; performing joint training for a dialogue understanding pre-training task and a general pre-training task by using the dialogue understanding training data, to obtain a dialogue understanding model. According to the present disclosure, a model specially adapted for a dialogue understanding task may be obtained by training.
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12.发明申请公开(公告)号：US20220019743A1
公开(公告)日：2022-01-20
申请号：US17318577
申请日：2021-05-12
Inventor： Xuan OUYANG , Shuohuan WANG , Yu SUN
IPC: G06F40/30 , G06F40/237 , G06N20/00 , G06N5/04
Abstract: Technical solutions relate to the natural language processing field based on artificial intelligence. According to an embodiment, a multilingual semantic representation model is trained using a plurality of training language materials represented in a plurality of languages respectively, such that the multilingual semantic representation model learns the semantic representation capability of each language; a corresponding mixed-language language material is generated for each of the plurality of training language materials, and the mixed-language language material includes language materials in at least two languages; and the multilingual semantic representation model is trained using each mixed-language language material and the corresponding training language material, such that the multilingual semantic representation model learns semantic alignment information of different languages.
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13.发明申请公开(公告)号：US20210374344A1
公开(公告)日：2021-12-02
申请号：US17094943
申请日：2020-11-11
Inventor： Shuohuan WANG , Chao PANG , Yu SUN
IPC: G06F40/284 , G06N20/00 , G06F16/23 , G06F7/08
Abstract: A method for resource sorting, a method for training a sorting model and corresponding apparatuses which relate to the technical field of natural language processing under artificial intelligence are disclosed. The method according to some embodiments includes: forming an input sequence in order with an item to be matched and information of candidate resources; performing Embedding processing on each Token in the input sequence, the Embedding processing including: word Embedding, position Embedding and statement Embedding; and inputting result of the Embedding processing in a sorting model to obtain sorting scores of the sorting model for the candidate resources, the sorting model is obtained by pre-training of a Transformer model.
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公开(公告)号：US20210374334A1
公开(公告)日：2021-12-02
申请号：US17117211
申请日：2020-12-10
Abstract: A method for training a language model, an electronic device and a readable storage medium, which relate to the field of natural language processing technologies in artificial intelligence, are disclosed. The method may include pre-training the language model using preset text language materials in a corpus; replacing at least one word in a sample text language material with a word mask respectively to obtain a sample text language material including at least one word mask; inputting the sample text language material including the at least one word mask into the language model, and outputting a context vector of each of the at least one word mask via the language model; determining a word vector corresponding to each word mask based on the context vector of the word mask and a word vector parameter matrix; and training the language model based on the word vector corresponding to each word mask.
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公开(公告)号：US20210248484A1
公开(公告)日：2021-08-12
申请号：US17205894
申请日：2021-03-18
Inventor： Shuohuan WANG , Siyu DING , Yu SUN
IPC: G06N5/02 , G06K9/62 , G06F40/279
Abstract: The disclosure discloses a method and an apparatus for generating a semantic representation model, and a storage medium. The detailed implementation includes: performing recognition and segmentation on the original text included in an original text set to obtain knowledge units and non-knowledge units in the original text; performing knowledge unit-level disorder processing on the knowledge units and the non-knowledge units in the original text to obtain a disorder text; generating a training text set based on the character attribute of each character in the disorder text; and training an initial semantic representation model by employing the training text set to generate the semantic representation model.
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Patent Agency Ranking
公开(公告)号：US20210397780A1
公开(公告)日：2021-12-23
申请号：US17405813
申请日：2021-08-18
Inventor： Chao PANG , Shuohuan WANG , Yu SUN , Zhi LI
IPC: G06F40/166 , G06K9/46 , G06K9/62 , G06N20/00
Abstract: A method for correcting an error in a text, an electronic device, and a storage medium are provided. The method includes: obtaining an original text; obtaining a training text by preprocessing the original text; extracting a plurality of feature vectors corresponding to each word in the training text; obtaining an input vector by processing the plurality of feature vectors; obtaining a target text by inputting the input vector into a text error correction model; and adjusting parameters of the text error correction model based on a difference between the target text and the original text.
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公开(公告)号：US20210374352A1
公开(公告)日：2021-12-02
申请号：US16951702
申请日：2020-11-18
IPC: G06F40/30 , G06F40/166 , G06F40/279 , G06N20/00
Abstract: A method for training a language model based on various word vectors, a device and a medium, which relate to the field of natural language processing technologies in artificial intelligence, are disclosed. An implementation includes inputting a first sample text language material including a first word mask into the language model, and outputting a context vector of the first word mask via the language model; acquiring a first probability distribution matrix of the first word mask based on the context vector of the first word mask and a first word vector parameter matrix, and a second probability distribution matrix of the first word mask based on the context vector of the first word mask and a second word vector parameter matrix; and training the language model based on a word vector corresponding to the first word mask.
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18.发明申请公开(公告)号：US20210182498A1
公开(公告)日：2021-06-17
申请号：US16885358
申请日：2020-05-28
Inventor： Yu SUN , Haifeng WANG , Shuohuan WANG , Yukun LI , Shikun FENG , Hao TIAN , Hua WU
Abstract: The present disclosure provides a method, apparatus, electronic device and storage medium for processing a semantic representation model, and relates to the field of artificial intelligence technologies. A specific implementation solution is: collecting a training corpus set including a plurality of training corpuses; training the semantic representation model using the training corpus set based on at least one of lexicon, grammar and semantics. In the present disclosure, by building the unsupervised or weakly-supervised training task at three different levels, namely, lexicon, grammar and semantics, the semantic representation model is enabled to learn knowledge at levels of lexicon, grammar and semantics from massive data, enhance the capability of universal semantic representation and improve the processing effect of the NLP task.
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公开(公告)号：US20190065507A1
公开(公告)日：2019-02-28
申请号：US16054920
申请日：2018-08-03
Inventor： Shuohuan WANG , Yu SUN , Dianhai YU
Abstract: Embodiments of the present disclosure disclose a method and apparatus for processing information. A specific implementation of the method includes: acquiring a search result set related to a search statement inputted by a user; parsing the search statement to generate a first syntax tree, and parsing a search result in the search result set to generate a second syntax tree set; calculating a similarity between the search statement and the search result in the search result set using a pre-trained semantic matching model on the basis of the first syntax tree and the second syntax tree set, the semantic matching model being used to determine the similarity between the syntax trees; and sorting the search result in the search result set on the basis of the similarity between the search statement and the search result in the search result set, and pushing the sorted search result set to the user.
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公开(公告)号：US20190065506A1
公开(公告)日：2019-02-28
申请号：US16054842
申请日：2018-08-03
Inventor： Yukun LI , Yi LIU , Yu SUN , Dianhai YU
Abstract: Embodiments of the present disclosure disclose a search method and apparatus based on artificial intelligence. A specific implementation of the method comprises: acquiring at least one candidate document related to a query sentence; determining a query word vector sequence corresponding to a segmented word sequence of the query sentence, and determining a candidate document word vector sequence corresponding to a segmented word sequence of each candidate document in the at least one candidate document; performing a similarity calculation for each candidate document in the at least one candidate document; selecting, in a descending order of similarities between the candidate document and the query sentence, a preset number of candidate documents from the at least one candidate document as a search result.
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