Abstract:
The present disclosure discloses an apparatus and method for distributedly training a model, an electronic device, and a computer readable storage medium. The apparatus may include: a distributed reader, a distributed trainer and a distributed parameter server that are mutually independent. A reader in the distributed reader is configured to acquire a training sample, and load the acquired training sample to a corresponding trainer in the distributed trainer; the trainer in the distributed trainer is configured to perform model training based on the loaded training sample to obtain gradient information; and a parameter server in the distributed parameter server is configured to update a parameter of an initial model based on the gradient information of the distributed trainer to obtain a trained target model.
Abstract:
A method for human-machine interaction based on a neural network is provided. The method includes: providing a user input as a first input for a neural network system; providing the user input to a conversation control system different from the neural network system; processing the user input by the conversation control system based on information relevant to the user input; providing a processing result of the conversation control system as second input for the neural network system; and generating, by the neural network system, a reply to the user input based on the first and second input.
Abstract:
Embodiments of the present disclosure provide a method and apparatus for performing a structured extraction on a text, a device and a storage medium. The method may include: performing a text detection on an entity text image to obtain a position and content of a text line of the entity text image; extracting multivariate information of the text line based on the position and the content of the text line; performing a feature fusion on the multivariate information of the text line to obtain a multimodal fusion feature of the text line; performing category and relationship reasoning based on the multimodal fusion feature of the text line to obtain a category and a relationship probability matrix of the text line; and constructing structured information of the entity text image based on the category and the relationship probability matrix of the text line.
Abstract:
A conversation processing method and apparatus based on artificial intelligence, a device and a computer-readable storage medium. The disclosure embodiments, enable the user feedback information provided by conversation service conducted by the user to model conversation understanding system, then according to the user feedback information, perform adjustment processing for a service state of the model conversation understanding system, to obtain an adjustment state of the model conversation understanding system so that it is possible to execute the conversation service with the model conversation understanding system, based on the adjustment state. Since a fault-tolerant and fault-correcting mechanism is provided, it is possible to adjust the understanding capability of the model conversation understanding system in real time and thereby effectively improve the reliability of conversation by collecting the user's user feedback information, and then adjusting the service state of the model conversation understanding system in time based on the user feedback information.
Abstract:
The present application discloses a monitoring method and apparatus. A specific implementation of the method comprises: reading information about monitoring data acquisition methods of monitored objects, the monitoring data acquisition method comprising an active acquisition method and a passive acquisition method; executing following steps for each of the monitored objects having the active acquisition method as the monitoring data acquisition method: generating a monitoring data acquisition task of the monitored object; determining a monitoring data acquisition frequency of the monitored object; and adding the monitoring data acquisition task to to-be-executed monitoring data acquisition task sets in a defined period corresponding to the monitoring data acquisition frequency; executing, in successive defined periods, monitoring data acquisition tasks in the corresponding to-be-executed monitoring data acquisition task sets; and parsing acquired monitoring data of the monitored objects to generate a monitoring result. The implementation solves the problem of high system resource occupation and waste of system resources during the monitoring process.
Abstract:
This disclosure discloses a method and apparatus for monitoring a message transmission frequency in a robot operating system. A specific implementation of the method includes: writing to-be-transmitted messages, into a pre-allocated memory; obtaining time points when the to-be-transmitted messages are written into the memory, and recording the time points in a preset time point list; determining a message transmission frequency within a preset time interval based on the time points in the time point list; and comparing the message transmission frequency with a preset message transmission frequency threshold, and generating monitoring information based on a comparing result. This implementation monitors the message transmission frequency of a process to thereby avoid information codes related to monitoring of each application from being added to the application so as to reduce the program debuging cost, and improve the monitoring efficiency.
Abstract:
Disclosed are a method and a device for expanding data of a bilingual corpus. The method for expanding data of a bilingual corpus includes: searching, in a source language-pivot language corpus, for at least one first pivot language phrase semantically matching a first source language phrase; searching, in the source language-pivot language corpus, for at least one second source language phrase semantically matching each of the first pivot language phrases to form a source language phrase set by the second source language phrases; searching, in a pivot language-target language corpus, for at least one first target language phrase semantically matching each of the first pivot language phrases to form a target language phrase set by the first target language phrases; combining the second source language phrases in the source language phrase set with the first target language phrases in the target language phrase set, so as to form at least one phrase pair in which a source language phrase and a target language phrase semantically match; and storing the formed at least one phrase pair in which the source language phrase and the target language phrase semantically match into a source language-target language corpus. Data in a bilingual corpus is expanded, so that the problem of data sparseness in the bilingual corpus is solved.
Abstract:
The present application discloses a method and device for establishing communication connection. An embodiment of the method includes: selecting a predetermined number of servers from a server cluster to form a backup server cluster, the server cluster including at least one server adapted to implement a given service; obtaining communication information of each backup server in the backup server cluster, and selecting a backup server from the backup server cluster as a master server based on the communication information of the backup server; and sending the communication information of the master server to controlled equipment controlled by the server cluster to establish communication connection between the master server and the controlled equipment. The embodiment solves a problem of reliability raised when main server abnormally quits or restarts during the operation of a system.
Abstract:
Disclosed are a method and a device for expanding data of a bilingual corpus. The method for expanding data of a bilingual corpus includes: searching, in a source language-pivot language corpus, for at least one first pivot language phrase semantically matching a first source language phrase; searching, in the source language-pivot language corpus, for at least one second source language phrase semantically matching each of the first pivot language phrases to form a source language phrase set by the second source language phrases; searching, in a pivot language-target language corpus, for at least one first target language phrase semantically matching each of the first pivot language phrases to form a target language phrase set by the first target language phrases; combining the second source language phrases in the source language phrase set with the first target language phrases in the target language phrase set, so as to form at least one phrase pair in which a source language phrase and a target language phrase semantically match; and storing the formed at least one phrase pair in which the source language phrase and the target language phrase semantically match into a source language-target language corpus. Data in a bilingual corpus is expanded, so that the problem of data sparseness in the bilingual corpus is solved.
Abstract:
Disclosed are on-line voice translation method and device. The method comprises: conducting voice recognition on first voice information input by a first user, so as to obtain first recognition information; prompting the first user to confirm the first recognition information; translating the confirmed first recognition information to obtain and output first translation information; extracting, according to second information which is fed back by a second user, associated information corresponding to the second information; and correcting the first translation information according to the associated information and outputting the corrected translation information. By means of the on-line voice translation method and device, smooth communication can be ensured in cross-language exchanges.