Systems and methods for providing a sociolinguistic virtual assistant

1. A system for providing a sociolinguistic virtual assistant, comprising:

a communication device;

a processing device;

a storage device;

the communication device being configured to:

receive input data from at least one user device associated with at least one user and transmit the input data to the processing device;

receive a command from the at least one user via the at least one user device and transmit the command to the processing device;

the processing device being configured to:

process the input data using a natural language processing algorithm, the natural language processing algorithm being configured to generate semantic data based on the input data and perform sentiment analysis associated with the input data, wherein the sentiment analysis is based on emotional and cognitive responses of the at least one user;

categorize the semantic data based on psych-sociological categorizations associated with the at least one user, wherein the psych-sociological categorizations are based on personality and value of the at least one user;

analyze the command from the at least one user to identify a task associated with the command;

generate a response based on identification of the task associated with the command;

execute the task associated with the command using categorized semantic data, to derive a result;

the storage device being configured to store the categorized semantic data; and

the communication device being further configured to:

transmit the response to the at least one user device; and

transmit the result to the at least one user device.

2. The system for providing a sociolinguistic virtual assistant as claimed in claim 1 , wherein the processing device is further configured to:

split the semantic data into a training data set and a validation data set;

create a training model using the training data set;

optimize the training model using the validation data set; and

refresh the semantic data based on optimized training model.

3. The system for providing a sociolinguistic virtual assistant as claimed in claim 2 , wherein three fourths of the semantic data are used to form the training data set, while one fourth of the semantic data is used to form the validation data set.

4. The system for providing a sociolinguistic virtual assistant as claimed in claim 3 , wherein the input data is voice data from diasporic, migrant, or secret community sources.

5. The system for providing a sociolinguistic virtual assistant as claimed in claim 1 , wherein the communication device, the processing device, and the storage device are provided in a cloud computing environment.

6. The system for providing a sociolinguistic virtual assistant as claimed in claim 1 , wherein the command comprises a voice command, a keypad input command, a touch input command, and a gesture input command.

7. The system for providing a sociolinguistic virtual assistant as claimed in claim 1 , wherein the response indicates that the task is being executed.

8. The system for providing a sociolinguistic virtual assistant as claimed in claim 1 , wherein the input data is encrypted before being transmitted to the processing device and decrypted before being processed using the natural language processing algorithm.

9. A method for providing a sociolinguistic virtual assistant, comprising the steps of:

receiving input data from at least one user device associated with at least one user;

receiving a command from the at least one user via the at least one user device;

processing the input data using a natural language processing algorithm, the natural language processing algorithm being configured to generate semantic data based on the input data and perform sentiment analysis associated with the input data, wherein the sentiment analysis is based on emotional and cognitive responses of the at least one user;

categorizing the semantic data based on psych-sociological categorizations associated with the at least one user, wherein the psych-sociological categorizations are based on personality and value of the at least one user;

analyzing the command from the at least one user to identify a task associated with the command;

generating a response based on identification of the task associated with the command;

transmitting the response to the at least one user device;

executing the task associated with the command using categorized semantic data, to derive a result;

storing the categorized semantic data; and

transmitting the result to the at least one user device.

10. The method for providing a sociolinguistic virtual assistant as claimed in claim 9 , wherein processing the input data using a natural language processing algorithm comprising the steps of:

splitting the semantic data into a training data set and a validation data set;

creating a training model using the training data set;

optimizing the training model using the validation data set; and

refreshing the semantic data based on optimized training model.

11. The method for providing a sociolinguistic virtual assistant as claimed in claim 10 , wherein three fourths of the semantic data are used to form the training data set, while one fourth of the semantic data is used to form the validation data set.

12. The method for providing a sociolinguistic virtual assistant as claimed in claim 11 , wherein the input data is voice data from diasporic, migrant, or secret community sources.

13. The method for providing a sociolinguistic virtual assistant as claimed in claim 9 , wherein the command comprises a voice command, a keypad input command, a touch input command, and a gesture input command.

14. The method for providing a sociolinguistic virtual assistant as claimed in claim 9 , wherein the response indicates that the task is being executed.

15. The method for providing a sociolinguistic virtual assistant as claimed in claim 9 , wherein the input data is encrypted after being received and decrypted before being processed using the natural language processing algorithm.