Comparing Spoken Languages using Paninian System of Sounds and Finite State Machines

TL;DR

This paper proposes a novel ecosystem model for linguistic development centered on Sanskrit, using Paninian phonetics and finite state machines to compare languages and challenge traditional language family classifications.

Contribution

It introduces a new approach combining Paninian phonetic mapping with finite automata to analyze and compare languages, offering an alternative to the traditional family tree model.

Findings

Sanskrit is positioned at the core of a new linguistic ecosystem model.

Words across languages are represented as state transitions on a phonetic map.

The model enables detailed comparison of vocabulary and phonological features.

Abstract

The study of spoken languages comprises phonology, morphology, and grammar. The languages can be classified as root languages, inflectional languages, and stem languages. In addition, languages continually change over time and space by picking isoglosses, as speakers move from region to/through region. All these factors lead to the formation of vocabulary, which has commonality/similarity across languages as well as distinct and subtle differences among them. Comparison of vocabularies across languages and detailed analysis has led to the hypothesis of language families. In particular, in the view of Western linguists, Vedic Sanskrit is a daughter language, part of the Indo-Iranian branch of the Indo-European Language family, and Dravidian Languages belong to an entirely different family. These and such conclusions are reexamined in this paper. Based on our study and analysis, we propose an Ecosystem Model for Linguistic Development with Sanskrit at the core, in place of the widely accepted family tree model. To that end, we leverage the Paninian system of sounds to construct a phonetic map. Then we represent words across languages as state transitions on the phonetic map and construct corresponding Morphological Finite Automata (MFA) that accept groups of words. Regardless of whether the contribution of this paper is significant or minor, it is an important step in challenging policy-driven research that has plagued this field.