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公开(公告)号：US20200250377A1
公开(公告)日：2020-08-06
申请号：US16856450
申请日：2020-04-23
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xin Jiang , Lifeng Shang , Hang Li , Zichao Li
IPC: G06F40/289
Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.
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公开(公告)号：US20250141431A1
公开(公告)日：2025-05-01
申请号：US19005875
申请日：2024-12-30
Abstract: A surface acoustic wave filter includes a support substrate with a first acoustic velocity layer disposed above. The first acoustic velocity layer is silicon dioxide with a piezoelectric layer above. Euler angles of a cut of the piezoelectric layer are (−5° to 5°, 81° to 83°, 85° to 95°), and an interdigital electrode is disposed above the piezoelectric layer. A second acoustic velocity layer included between the first acoustic velocity layer and the support substrate; and a material of the second acoustic velocity layer is aluminum nitride or silicon nitride, where a longitudinal wave acoustic velocity in the first acoustic velocity layer is lower than a longitudinal wave acoustic velocity in the piezoelectric layer, and a longitudinal wave acoustic velocity in the second acoustic velocity layer is higher than the longitudinal wave acoustic velocity in the piezoelectric layer.
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公开(公告)号：US12182507B2
公开(公告)日：2024-12-31
申请号：US17682145
申请日：2022-02-28
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Yichun Yin , Lifeng Shang , Xin Jiang , Xiao Chen
IPC: G06F40/216 , G06F40/166 , G06F40/279 , G06F40/30 , G06N3/045 , G06N3/084
Abstract: A text processing model training method, and a text processing method and apparatus in the natural language processing field in the artificial intelligence field are disclosed. The training method includes: obtaining training text; separately inputting the training text into a teacher model and a student model to obtain sample data output by the teacher model and prediction data output by the student model; the sample data includes a sample semantic feature and a sample label; the prediction data includes a prediction semantic feature and a prediction label; and the teacher model is a pre-trained language model used for text classification; and training a model parameter of the student model based on the sample data and the prediction data, to obtain a target student model. The method enables the student model to effectively perform knowledge transfer, thereby improving accuracy of a text processing result of the student model.
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14.发明授权公开(公告)号：US12039976B2
公开(公告)日：2024-07-16
申请号：US17171166
申请日：2021-02-09
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Yingtao Li , Xin Jiang , Xiao Chen , Baofeng Zhang , Li Qian
CPC classification number: G10L15/22 , G06F40/35 , G10L15/16 , G10L15/1815 , G06F40/30 , G10L2015/223 , G10L2015/227 , G10L2015/228
Abstract: The application relates to the field of man-machine interaction in artificial intelligence and provides a multi-task processing method. The method includes the following operations: determining a first task based on request information entered by a user; obtaining key information corresponding to the first task and executing the first task, where the key information includes one or more slots and values of the one or more slots; storing task status information of the first task, where the task status information includes the key information; and predicting and initiating a second task based on the task status information of the first task. A man-machine interaction system may predict a next task based on the stored task status information, and actively initiate the predicted task. This improves intelligence and efficiency of multi-task processing by the man-machine interaction system.
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公开(公告)号：US20240185086A1
公开(公告)日：2024-06-06
申请号：US18443052
申请日：2024-02-15
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Lu HOU , Haoli Bai , Lifeng Shang , Xin Jiang , Li Qian
Abstract: This disclosure relates to the field of artificial intelligence, and provides model distillation methods and apparatuses. In an implementation, a method including: obtaining first input data and second input data from a second computing node, wherein the first input data is output data of the third sub-model, and the second input data is output data processed by the fourth sub-model, processing the first input data by using the first sub-model, to obtain a first intermediate output, processing the second input data by using the second sub-model, to obtain a second intermediate output, wherein the first intermediate output and the second intermediate output are used to determine a first gradient, and distilling the first sub-model based on the first gradient, to obtain an updated first sub-model.
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Patent Agency Ranking
公开(公告)号：US20240127000A1
公开(公告)日：2024-04-18
申请号：US17958080
申请日：2022-09-30
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Yichun Yin , Lifeng Shang , Cheng Chen , Xin Jiang , Xiao Chen , Qun Liu
Abstract: A computer-implemented method is provided for model training performed by a processing system. The method comprises determining a set of first weights based on a first matrix associated with a source model, determining a set of second weights based on the set of first weights, forming a second matrix associated with a target model based on the set of first weights and the set of second weights, initializing the target model based on the second matrix, and training the target model.
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公开(公告)号：US11586814B2
公开(公告)日：2023-02-21
申请号：US16856450
申请日：2020-04-23
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xin Jiang , Lifeng Shang , Hang Li , Zichao Li
IPC: G06F40/289 , G06F40/237
Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.
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公开(公告)号：US20230017274A1
公开(公告)日：2023-01-19
申请号：US17952401
申请日：2022-09-26
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Abstract: Embodiments of this application provide a voice interaction method and an electronic device, and relate to the field of artificial intelligence AI technologies and the field of voice processing technologies. A specific solution includes: An electronic device may receive first voice information sent by a second user, and the electronic device recognizes the first voice information in response to the first voice information. The first voice information is used to request a voice conversation with a first user. The electronic device may have, on a basis that the electronic device recognizes that the first voice information is voice information of the second user, a voice conversation with the second user by imitating a voice of the first user and in a mode in which the first user has a voice conversation with the second user.
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19.发明授权公开(公告)号：US12175188B2
公开(公告)日：2024-12-24
申请号：US17701775
申请日：2022-03-23
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Lihua Qian , Yinpeng Guo , Lin Qiu , Weinan Zhang , Xin Jiang , Yong Yu
IPC: G06F40/40 , G06F40/166 , G06F40/20 , G06F40/30
Abstract: This disclosure relates to a natural language processing technology, and provides a sentence paraphrase method and apparatus. The method includes: paraphrasing an input sentence by using a sentence paraphrase model, to generate a plurality of candidate paraphrased sentences; and determining a similarity between each of the plurality of candidate paraphrased sentences and the input sentence, to obtain an output sentence whose similarity to the input sentence is greater than or equal to a preset threshold, where each of a plurality of paraphrased sentence generators in the sentence paraphrase model includes one neural network, the plurality of paraphrased sentence generators are trained by using source information and similarity information as a first reward, and the paraphrased sentence is obtained by paraphrasing the training sentence by using the plurality of paraphrased sentence generators. In the sentence paraphrase method, diversity of a paraphrased sentence and quality of the paraphrased sentence can be improved.
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公开(公告)号：US20240386274A1
公开(公告)日：2024-11-21
申请号：US18787328
申请日：2024-07-29
Applicant: Huawei Technologies Co., Ltd.
Inventor： Pingyi Zhou , Xiaozhe Ren , Yasheng Wang , Bin He , Xinfan Meng , Xin Jiang
IPC: G06N3/08
Abstract: A data processing method includes processing target data through a target neural network to obtain a data processing result, where a target header of the target neural network is used to process, through a first transformation matrix, a first vector corresponding to first subdata, and process, through a second transformation matrix, a second vector corresponding to the first subdata, where the first vector corresponds to position information of the first subdata in the target data, and the second vector corresponds to semantic information of the first subdata.
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