Paper Title
NL2SQL: A Review on the Conversion of Natural Language Queries to SQL Queries

Abstract
Recent years have seen tremendous progress in Natural Language Processing(NLP), especially within the area of text-to-SQL command generation. This review study offers a complete summary of the latest approaches and strategies used to translate natural language queries into structured SQL commands. Enabling intuitive and efficient interaction with relational databases requires the ability to bridge the gap between human language and database query languages.Despite its potential, the field of NLP to SQL is still developing, and a number of issues must be resolved before it can be extensively used. Natural language inquiries can be ambiguous, which makes it challenging for NLP systems to accurately decipher their meaning. Another difficulty is that SQL is a complicated language, making it challenging to create NLP systems that can produce accurate and effective SQL queries. Keywords -Natural Language Processing(NLP), SQL, Text to SQL Query Generation,Text Pre-Processing, RNN, LSTM, Deep Learning, Machine Learning, Database(DB)