公开(公告)号：US20220215159A1

公开(公告)日：2022-07-07

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: G06F40/166 ,  G06F40/20 ,  G06F40/40

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.

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.