Huawei Technologies Co., Limited

Jiansheng Wei

Lei Chen

Tao Li

Liqun Deng

Junhua Zhu

Wenhua Sun

Yasheng Wang

Guowei Huang

Yang Zhang

Maosheng Huang

Heng Liao

Xiaofei Zhang

Wenjie Liu

Dawei Huo

Yulong Zeng

Sixiao Yang

Anqi Cui

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.

Missing semantics complementing method and apparatus

A natural language processing method includes obtaining a to-be-processed phrase, where the to-be-processed phrase includes M words, determining polarity characteristic information of m to-be-processed words in the M words, where polarity characteristic information of an iword in the m to-be-processed words includes n polarity characteristic values, and each polarity characteristic value corresponds to one sentiment polarity, determining a polarity characteristic vector of the to-be-processed phrase based on the polarity characteristic information of the m to-be-processed words, where the polarity characteristic vector includes n groups of components in a one-to-one correspondence with n sentiment polarities, and determining a sentiment polarity of the to-be-processed phrase based on the polarity characteristic vector of the to-be-processed phrase using a preset classifier, and outputting the sentiment polarity.

Natural language processing method and apparatus

The present invention provides a robot control method, and the method includes: collecting interaction information of a companion target, and obtaining digital person information of a companion person (), where the interaction information includes interaction information of a sound or an action of the companion target toward the robot, and the digital person information includes a set of digitized information of the companion person; and determining, by using the interaction information and the digital person information, a manner of interacting with the companion target (); generating, based on the digital person information of the companion person and by using a machine learning algorithm, an interaction content corresponding to the interaction manner (); and generating a response action toward the companion target based on the interaction manner and the interaction content ().

Robot control method and companion robot

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.

Speech synthesis method and device

A control method for performing a multi-table join operation and a corresponding apparatus are disclosed. Fields in a table whose fields participating in a theta join operation and used in the query statement meet a first preset condition are decomposed, to obtain a plurality of first field groups, so that the theta join operation can be implemented in steps in a form of the plurality of field groups. This can reduce a data amount of Cartesian product calculation during one join operation, greatly reduce network transmission overheads, computing overheads, and memory overheads, and improve execution efficiency.

Control method for performing multi-table join operation and corresponding apparatus

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.

Mapreduce job resource sizing using assessment models

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.

Resource allocation method and apparatus for gene analysis

Embodiments of the present invention provide a data object processing method and apparatus, which can divide a data object into one or more blocks; calculate a sample compression ratio of each block, aggregate neighboring consecutive blocks with a same sample compression ratio characteristic into one data segment, and obtain the sample compression ratio of each of the data segments; and select, according to a length range to which a length of each of the data segments belongs and a compression ratio range to which the sample compression ratio of each of the data segments belongs, an expected length to divide the data segment into data chunks, where the sample compression ratio of each of the data segments uniquely belongs to one of the compression ratio ranges, and the length of each of the data segments uniquely belongs to one of the length ranges.

Data object processing method and apparatus

A method and an apparatus for calculating an estimated data compression ratio relate to the field of data processing technologies. In the solutions, an estimated data compression ratio is calculated using a related indicator that represents a distribution pattern of symbols in a symbol sequence, where the related indicator that represents the distribution pattern of the symbols in the symbol sequence is relatively closely related to the estimated data compression ratio.

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Shenzhen, China

Jiansheng Wei