公开(公告)号：US20210287657A1

公开(公告)日：2021-09-16

申请号：US17225376

申请日：2021-04-08

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Liqun Deng ,  Jiansheng Wei ,  Wenhua Sun

IPC: G10L13/10 ,  G10L25/63 ,  G10L13/033 ,  G10L13/047

Abstract: In a speech synthesis method, an emotion intensity feature vector is set for a target synthesis text, an acoustic feature vector corresponding to an emotion intensity is generated based on the emotion intensity feature vector by using an acoustic model, and a speech corresponding to the emotion intensity is synthesized based on the acoustic feature vector. The emotion intensity feature vector is continuously adjustable, and emotion speeches of different intensities can be generated based on values of different emotion intensity feature vectors, so that emotion types of a synthesized speech are more diversified. This application may be applied to a human-computer interaction process in the artificial intelligence (AI) field, to perform intelligent emotion speech synthesis.

公开(公告)号：US12135941B2

公开(公告)日：2024-11-05

申请号：US17530197

申请日：2021-11-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Yulong Zeng ,  Jiansheng Wei ,  Yasheng Wang ,  Liqun Deng ,  Anqi Cui

IPC: G06F40/30 ,  G06F40/289 ,  G06N5/01

Abstract: A missing semantics complementing method in the field of natural language processing in the artificial intelligence field is provided. The method includes: obtaining a question statement and a historical dialog statement; resolving a to-be-resolved item in the question statement based on the historical dialog statement and location information of the to-be-resolved item, to obtain a resolved question statement; determining whether a component in the question statement is ellipted, and if a component in the question statement is ellipted, complementing the ellipted component based on the historical dialog statement, to obtain a question statement after ellipsis resolution; merging the resolved question statement and the question statement after ellipsis resolution, to obtain a merged question statement; and determining a target complemented question statement from the resolved question statement, the question statement after ellipsis resolution, and the merged question statement.

公开(公告)号：US11003507B2

公开(公告)日：2021-05-11

申请号：US16369564

申请日：2019-03-29

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Guowei Huang ,  Liqun Deng ,  Jiansheng Wei

IPC: G06F9/50

Abstract: The present disclosure relates to computing resource allocation methods, devices, and systems. One example system includes a management node and a target computing node. The management node is configured to obtain M computing tasks and establish a resource assessment model, and send one or more computing tasks of the M computing tasks and information about the resource assessment model to the target computing node. The target computing node is configured to receive the one or more computing tasks and the information about the resource assessment model, substitute input data of a particular computing stage of a target task into the resource assessment model to compute a resource size required for the particular computing stage, and compute the input data by using a computing resource that is of the resource size and that is in a preset resource pool.

公开(公告)号：US10853135B2

公开(公告)日：2020-12-01

申请号：US16153099

申请日：2018-10-05

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Jiansheng Wei ,  Guowei Huang ,  Liqun Deng

IPC: G06F9/50 ,  G16B50/30 ,  G16B20/00 ,  G16B30/10 ,  G06F9/52

Abstract: The present disclosure relates to a resource allocation method for gene analysis. In one example method, a parameter value that is of the target chromosome region and that is used for resource allocation is obtained according to a sequenced read in a target chromosome region. A computing resource is allocated, according to the parameter value that is of the target chromosome region and that is used for resource allocation, to an operation in a cleansing and variant calling task that is in the gene analysis and that is performed on the sequenced read in the target chromosome region.

公开(公告)号：US20160357740A1

公开(公告)日：2016-12-08

申请号：US15241909

申请日：2016-08-19

Applicant: Huawei Technologies Co., Ltd.

Inventor： Liqun Deng ,  Junhua Zhu

IPC: G06F17/30

CPC classification number: G06F17/3012 ,  G06F3/061 ,  G06F3/0638 ,  G06F3/067 ,  G06F17/30091 ,  G06F17/30185 ,  G06F17/30194 ,  G06F17/30238

Abstract: A metadata updating method based on columnar storage in a distributed file system includes acquiring to-be-updated metadata in a data table, splitting data records of the data table into multiple row groups on a row basis, converting the data table into global file metadata and multiple row group files, where the row group file includes an actual data block, a data index block, a local metadata block, a metadata index block, and a file footer, determining whether the to-be-updated metadata belongs to the global file metadata, updating local metadata when the to-be-updated metadata does not belong to the global file metadata, and adding an updated local metadata block, an updated metadata index block, and an updated file footer to the multiple row group files according to updated local metadata. Dynamic updating of metadata saves time of executing an updating operation of this type and needed computing resources.

Abstract translation: 基于分布式文件系统中的柱状存储的元数据更新方法包括获取数据表中的要更新的元数据，将数据表的数据记录划分为行的多个行组，将数据表转换为全局文件元数据 以及多个行组文件，其中行组文件包括实际数据块，数据索引块，本地元数据块，元数据索引块和文件页脚，确定要更新的元数据是否属于全局 文件元数据，当待更新的元数据不属于全局文件元数据时，更新本地元数据，并且根据更新的本地元数据块，更新的元数据索引块和更新的文件页脚添加到多个行组文件 更新的本地元数据。 元数据的动态更新节省了执行此类更新操作的时间，并需要计算资源。

公开(公告)号：US11282498B2

公开(公告)日：2022-03-22

申请号：US16944863

申请日：2020-07-31

Applicant: Huawei Technologies Co., Ltd.

Inventor： Liqun Deng ,  Yuezhi Hu ,  Zhanlei Yang ,  Wenhua Sun

IPC: G10L15/22 ,  G10L13/10 ,  G10L13/047

Abstract: A speech synthesis method and a speech synthesis apparatus to synthesize speeches of different emotional intensities in the field of artificial intelligence, where the method includes obtaining a target emotional type and a target emotional intensity parameter that correspond to an input text, determining a corresponding target emotional acoustic model based on the target emotional type and the target emotional intensity parameter, inputting a text feature of the input text into the target emotional acoustic model to obtain an acoustic feature of the input text, and synthesizing a target emotional speech based on the acoustic feature of the input text.

公开(公告)号：US20190156917A1

公开(公告)日：2019-05-23

申请号：US16251920

申请日：2019-01-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Chuanjian Liu ,  Liqun Deng ,  Guowei Huang

IPC: G16B30/10 ,  G16B40/10

Abstract: A data processing method includes traversing all sample fragments in a first sample set and collecting statistics about a first statistic of each basic element in a reference sample and included in the sample fragments, determining that a position of a basic element in the reference sample whose first statistic is less than a first threshold is a spacing position, dividing the reference sample into at least two reference sub-samples, traversing all the sample fragments in the first sample set and collecting statistics about a second statistic of each reference sub-sample of the reference sample and including the sample fragments, and combining adjacent reference sub-samples when a sum of second statistics of the adjacent reference sub-samples is less than a second threshold.

公开(公告)号：US20190156916A1

公开(公告)日：2019-05-23

申请号：US16251829

申请日：2019-01-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Liqun Deng ,  Guowei Huang ,  Jiansheng Wei

IPC: G16B30/10 ,  G06F17/27 ,  G06F9/48 ,  G06F9/38

Abstract: A data processing method includes distributing, by a computing node, a pasting back result sequence corresponding to a to-be-pasted-back deoxyribonucleic acid (DNA) read string to a pasting back result sequence set corresponding to a target chromosome region, when the quantity of the pasting back result sequences included in the pasting back result sequence set is greater than or equal to the pre-determined quantity threshold, dividing the pasting back result sequence set into k pasting back result sequence subsets according to a preset division rule, and dividing the target chromosome region into k chromosome subregions in a one-to-one correspondence to the k pasting back result sequence subsets, and further dividing a gene analysis task of the pasting back result sequence set into k gene analysis subtasks, and executing in parallel the k gene analysis subtasks.

公开(公告)号：US11361751B2

公开(公告)日：2022-06-14

申请号：US17225376

申请日：2021-04-08

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Liqun Deng ,  Jiansheng Wei ,  Wenhua Sun

IPC: G10L25/63 ,  G10L13/10 ,  G10L13/00 ,  G10L21/00 ,  G10L15/00 ,  G10L13/033 ,  G10L13/047

Abstract: In a speech synthesis method, an emotion intensity feature vector is set for a target synthesis text, an acoustic feature vector corresponding to an emotion intensity is generated based on the emotion intensity feature vector by using an acoustic model, and a speech corresponding to the emotion intensity is synthesized based on the acoustic feature vector. The emotion intensity feature vector is continuously adjustable, and emotion speeches of different intensities can be generated based on values of different emotion intensity feature vectors, so that emotion types of a synthesized speech are more diversified. This application may be applied to a human-computer interaction process in the artificial intelligence (AI) field, to perform intelligent emotion speech synthesis.

公开(公告)号：US10558498B2

公开(公告)日：2020-02-11

申请号：US15598696

申请日：2017-05-18

Applicant: Huawei Technologies Co., Ltd.

Inventor： Liqun Deng ,  Junhua Zhu

IPC: G06F9/46 ,  G06F9/50 ,  G06F9/48

Abstract: A method for scheduling a data flow task and an apparatus. The method includes: preprocessing a data flow task to obtain at least one subtask; classifying the subtask into a central processing unit (CPU) task group, a graphics processing unit (GPU) task group, or a to-be-determined task group; allocating the subtask to a working node; when the subtask belongs to the CPU task group, determining that a CPU executes the subtask; when the subtask belongs to the GPU task group, determining that a GPU executes the subtask; or when the subtask belongs to the to-be-determined task group, determining, according to costs of executing the subtask by a CPU and a GPU, a running platform (e.g., the CPU or the GPU) executes the subtask, where the cost includes duration of executing the subtask.