Huawei Technologies Co., Limited

Huawei Device Co., Ltd.

Xiyong Wang

Hongrui Jiang

Weijun Zheng

Junyang Zhou

Changzhu Li

Li Zhou

Wenmei Gao

Xiaojuan Li

Yahui Wang

Hao Jing

Junbin Liang

Tao Fan

Renzhi Yang

Jiyong Jiang

Mohan Liu

Huajun Cao

Kang Sun

Jinghua Sima

Yuying Zeng

An image recognition method and a terminal, where the method includes obtaining, by the terminal, an image file comprising a target object, recognizing, by the terminal, the target object based on an image recognition model in the terminal to obtain object category information of the target object, and storing, by the terminal, the object category information as first label information of the target object. Hence, image recognition efficiency of the terminal can be improved, and privacy of a terminal user can be effectively protected.

Image recognition method and terminal

A recommendation method applied to a terminal includes a rule platform with system-level permission, the rule platform is configured to save system resources and remind a user of a function of an application. The rule platform obtains a first event and a first rule related to the first event from a rule base. The rule platform includes the rule base including a rule and each rule includes a condition. The rule platform updates a matching status of a first condition corresponding to the first event in the first rule The terminal displays a recommendation result corresponding to the first rule when a matching status of each condition in the first rule indicates that the matching is successful. The first rule is one of the rule related to the first event.

Recommendation method and terminal

An image recognition method and a terminal, where the method includes obtaining, by the terminal, an image file including a target object recognizing, by the terminal, the target object based on an image recognition model in the terminal using a neural network computation apparatus in the terminal to obtain object category information of the target object, and storing, by the terminal, the object category information in the image file as first label information of the target object. Hence, image recognition efficiency of the terminal can be improved, and privacy of a terminal user can be effectively protected.

A data processing method and device, where the method includes obtaining a usage frequency value of software, compressing a target file of the software to obtain a compressed file when the usage frequency value is less than a preset usage frequency value, receiving a startup instruction for starting the software, querying the compressed file of the software, and decompressing the compressed file using a high-priority process to obtain the target file, where the high-priority process is performed as an essential highest-priority process relative to another process, and starting the software based on the target file.

Data processing method and device

A method and an apparatus for converting a speech-to-text in a multiparty call. Receiving speech-to-text requests sent by at least two terminals, where the speech-to-text requests include a first identifier and a second identifier; allocating a session to the at least two terminals, so that in the speech-to-text requests sent by the at least two terminals, terminals that have a same first identifier or a same second identifier have a same session; receiving, by using a packet-switched domain, a voice stream whose sampling rate is greater than 8 KHz and that is sent by at least one terminal in one multiparty call, where the multiparty call corresponds to one session; converting the voice stream into a text; and sending the text to a terminal in the multiparty call.

Method and apparatus for converting voice into text in multiparty call

Embodiments of the present invention relate to a method and an apparatus for optimizing a model applicable to pattern recognition, and a terminal device. The terminal device receives a universal model delivered by a server, where the universal model includes an original feature parameter; recognizes target information by using the universal model, and collects a plurality of local samples; when a model optimization condition is met, corrects the original feature parameter by using a first training algorithm to obtain a new feature parameter; and optimizes the universal model according to a second training algorithm and the new feature parameter, to obtain an optimized universal model. That is, in the present invention, the terminal device further optimizes, according to the collected local samples, the universal model received from the server to obtain a relatively personalized model applicable to pattern recognition.

Method and apparatus for optimizing model applicable to pattern recognition, and terminal device

A method is provided that includes: displaying, by the terminal, a randomly generated dynamic password on a display interface, and starting a voice receiving device of the terminal; obtaining by using the voice receiving device, voice information when a user reads the dynamic password, converting the voice information into a text password, and extracting a voiceprint feature of the voice information; and when the text password is the same as the dynamic password, determining terminal usage permission of the user according to a prestored correspondence between terminal usage permission and a voiceprint feature, and setting the display interface to an unlocked or locked state according to the determined terminal usage permission; or setting the display interface to a locked state when the text password is different from the dynamic password.

Apparatus and methods for improving terminal security

An information processing method and apparatus in the field of mobile communications technologies is provided. In the method, a first terminal obtains, during a call with a second terminal by using voice information sent by the second terminal, to-be-obtained information and object information of an object to which the to-be-obtained information belongs. The first terminal determines at least one category to which the to-be-obtained information belongs and determines a group that is in any category of the at least one category and corresponding to the object to which the to-be-obtained information belongs. The first terminal searches information in the corresponding group in any category for target information associated with the object information and processes the target information with no manual searching being performed.

Information processing method and apparatus

Embodiments of the present invention provide a voice identification method, which includes: obtaining voice data; obtaining a confidence value according to the voice data; obtaining a noise scenario according to the voice data; obtaining a confidence threshold corresponding to the noise scenario; and if the confidence value is greater than or equal to the confidence threshold, processing the voice data. An apparatus is also provided. The method and apparatus that flexibly adjust the confidence threshold according to the noise scenario greatly improve a voice identification rate under a noise environment.

Voice identification method and apparatus

Embodiments of the present invention provide a voice identification method, including: obtaining voice data; obtaining a first confidence value according to the voice data; obtaining a noise scenario according to the voice data; obtaining a second confidence value corresponding to the noise scenario according to the first confidence value; and if the second confidence value is greater than or equal to a pre-stored confidence threshold, processing the voice data. An apparatus is also provided. The method and apparatus that flexibly adjust the confidence value according to the noise scenario greatly improve a voice identification rate under a noise environment.

An information recognition method and apparatus are provided. The method includes receiving, by a terminal, voice information, extracting a voice feature from the voice information, performing matching calculation on the voice feature and a phoneme string corresponding to each candidate text in multiple candidate texts to obtain a recognition result, where the recognition result includes at least one command word and a label corresponding to the at least one command word, and recognizing, according to the label corresponding to the at least one command word, an operation instruction corresponding to the voice information. A terminal recognizes text information, which is corresponding to voice information input by a user, as an operation instruction.

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Shenzhen, China

Xiyong Wang