Multilingual command line interface bots enabled with a real-time language analysis service
The input of a user is monitored and a location of the user and a language of the user are detected. The input is converted to a text string in the detected user language and the converted text string is parsed into parsed tokens. A command line and correlated parameters indicated by the input are recognized based on the parsed tokens. The recognized command line with the assigned parameters is executed.
1 . A method comprising:
monitoring, using at least one hardware processor, input of a user;
detecting, using the at least one hardware processor, a location of the user and a language of the user;
converting, using the at least one hardware processor, the input to a text string in the detected user language;
parsing, using the at least one hardware processor, the converted text string into parsed tokens;
recognizing, using the at least one hardware processor, a command line and correlated parameters indicated by the input based on the parsed tokens;
executing the recognized command line with the assigned parameters;
verifying, using pre-defined rules, that results of executing the recognized command line validate that the recognized command line is an accurate conversion of the input; and
updating mappings of a human command to command line mapping repository based on results of the verifying operation.
2 . The method of claim 1 , further comprising assigning, using the at least one hardware processor, one or more variables of environment and attributes for the recognized command line and the correlated parameters.
3 . The method of claim 1 , wherein the assigning operation assigns a language of the user, a date format of the user, and a location of the user.
4 . The method of claim 1 , wherein the converting the input to the text string further comprises performing speech recognition on the input.
5 . The method of claim 1 , further comprising:
defining a framework of a Multilingual Command Line Interface Bot for supporting an intelligent voice control command line interface across different languages.
6 . The method of claim 1 , further comprising:
defining a data structure with related algorithms for tracking user voice commands and related parameters.
7 . The method of claim 1 , further comprising:
repeating the monitoring, detecting, converting, parsing, recognizing, and executing operations based on additional input, wherein the executing operation further comprises controlling a computer resource based on the additional input.
8 . The method of claim 1 , further comprising comparing a summary of the parsed text string to entries of the command line mapping repository to identify a most similar command line using an edit distance algorithm.
9 . A method comprising:
monitoring, using at least one hardware processor, input of a user;
detecting, using the at least one hardware processor, a location of the user and a language of the user;
converting, using the at least one hardware processor, the input to a text string in the detected user language;
parsing, using the at least one hardware processor, the converted text string into parsed tokens;
recognizing, using the at least one hardware processor, a command line and correlated parameters indicated by the input based on the parsed tokens;
executing the recognized command line with the assigned parameters;
verifying, using pre-defined rules, that results of executing the recognized command line validate that the recognized command line is an accurate conversion of the input;
enabling the user to configure settings and criteria of the method;
learning and generating a human command to command line mapping repository for one or more languages; and
adjusting, using a machine-based learner, the settings and criteria based on a result of the validation.
10 . The method of claim 9 , further comprising:
verifying, using pre-defined rules, that results of executing the recognized command line validate that the recognized command line is an accurate conversion of the input; and
revising, using the learner, the recognized command line in the command line mapping repository based on the result of the validation.
11 . The method of claim 9 , further comprising manually initializing the command line mapping repository with a set of available command lines and updating the mapping repository using machine learning as user input is processed.
12 . A computer program product, comprising:
one or more tangible computer-readable storage media and program instructions stored on at least one of the one or more tangible computer-readable storage media, the program instructions executable by a processor, the program instructions comprising:
monitoring, using at least one hardware processor, input of a user;
detecting, using the at least one hardware processor, a location of the user and a language of the user;
converting, using the at least one hardware processor, the input to a text string in the detected user language;
parsing, using the at least one hardware processor, the converted text string into parsed tokens;
recognizing, using the at least one hardware processor, a command line and correlated parameters indicated by the input based on the parsed tokens;
executing the recognized command line with the assigned parameters;
verifying, using pre-defined rules, that results of executing the recognized command line validate that the recognized command line is an accurate conversion of the input; and
updating mappings of a human command to command line mapping repository based on results of the verifying operation.
13 . A system comprising:
a memory; and
at least one processor, coupled to said memory, and operative to perform operations comprising:
monitoring, using at least one hardware processor, input of a user;
detecting, using the at least one hardware processor, a location of the user and a language of the user;
converting, using the at least one hardware processor, the input to a text string in the detected user language;
parsing, using the at least one hardware processor, the converted text string into parsed tokens;
recognizing, using the at least one hardware processor, a command line and correlated parameters indicated by the input based on the parsed tokens;
executing the recognized command line with the assigned parameters;
verifying, using pre-defined rules, that results of executing the recognized command line validate that the recognized command line is an accurate conversion of the input; and
updating mappings of a human command to command line mapping repository based on results of the verifying operation.
14 . The system of claim 13 , the operations further comprising assigning, using the at least one hardware processor, one or more variables of environment and attributes for the recognized command line and the correlated parameters.
15 . The system of claim 13 , wherein the converting the input to the text string further comprises performing speech recognition on the input.
16 . The system of claim 13 , the operations further comprising:
enabling the user to configure settings and criteria of the method;
learning and generating the human command to command line mapping repository for one or more languages; and
adjusting, using a machine-based learner, the settings and criteria based on a result of the validation.
17 . The system of claim 13 , the operations further comprising:
defining a framework of a Multilingual Command Line Interface Bot for supporting an intelligent voice control command line interface across different languages.
18 . The system of claim 13 , the operations further comprising:
repeating the monitoring, detecting, converting, parsing, recognizing, and executing operations based on additional input, wherein the executing operation further comprises controlling a computer resource based on the additional input.