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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM48778

Voice-Driven Natural Language to SQL Query Conversion Using NLP Techniques

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM48778

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM48778

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PSR

P. Shashank Reddy1

PR

P.Dhanush Reddy2

Og

O.Shiva ganesh3

MDV

Mrs.B.Vasundhara Devi Varanasi4

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Abstract

To get the accurate SQL queries in this application, input is given in the form of natural language, and using NLP techniques, relevant information is extracted to get SQL queries. This application is implemented for non-technical users, which is more user-friendly and has the capability to generate SQL code for complex queries and language with ambiguity. So, this application can be used by the individuals who have limited technical skills and who can enter the queries in the natural language. Even this application helps to generate the SQL code for those who do not have knowledge of SQL code. As per the user requirements, the user input is collected in the format of natural language and translated into SQL queries using algorithms from NLP algorithms. This application helps professionals in the business domain to save their efforts as well as time and analyze huge amounts of data by generating SQL queries automatically, as this application provides more accurate results for SQL query generation. Python libraries such as NLTK and SpaCy are used in this application programming.

KEYWORDS

SQL queries natural language natural language processing Python programming NLTK Spacy libraries.

Cite This Article

P. Shashank Reddy1, P.Dhanush Reddy2, O.Shiva ganesh3, Mrs.B.Vasundhara Devi Varanasi4, "Voice-Driven Natural Language to SQL Query Conversion Using NLP Techniques," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025. https://doi.org/10.55041/IJSREM48778

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Publication Date

5/26/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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