# A Computational Analysis of Natural Languages to Build a Sentence Structure Aware Artificial Neural Network

## TL;DR

This paper investigates language structures by comparing morphological features and develops a neural network that can identify languages based on sentence structure, revealing structural traits as key identifiers.

## Contribution

It introduces a method to analyze language similarity through morphology and sentence structure, and presents a neural network that classifies languages using sentence structure alone.

## Key findings

- Languages group by similarity in morphology and sentence structure.
- Sentence structure alone can distinguish between languages.
- Developed neural network successfully classifies languages based on sentence structure.

## Abstract

Natural languages are complexly structured entities. They exhibit characterising regularities that can be exploited to link them one another. In this work, I compare two morphological aspects of languages: Written Patterns and Sentence Structure. I show how languages spontaneously group by similarity in both analyses and derive an average language distance. Finally, exploiting Sentence Structure I developed an Artificial Neural Network capable of distinguishing languages suggesting that not only word roots but also grammatical sentence structure is a characterising trait which alone suffice to identify them.