On measuring linguistic intelligence

TL;DR

This paper introduces a novel measure called 'linguistic quotient' (LQ) to quantify a person's effective language proficiency, accounting for language similarities and proficiency levels, using a mathematical framework inspired by finance risk measures.

Contribution

It proposes a new LQ measure for language portfolios, grounded in properties from coherent risk measures, with an algorithm utilizing language classification trees.

Findings

The LQ measure accounts for language similarity and proficiency levels.

An algorithm for computing LQ using language classification trees is provided.

The method is implemented and available online at lingvometer.com.

Abstract

This work addresses the problem of measuring how many languages a person "effectively" speaks given that some of the languages are close to each other. In other words, to assign a meaningful number to her language portfolio. Intuition says that someone who speaks fluently Spanish and Portuguese is linguistically less proficient compared to someone who speaks fluently Spanish and Chinese since it takes more effort for a native Spanish speaker to learn Chinese than Portuguese. As the number of languages grows and their proficiency levels vary, it gets even more complicated to assign a score to a language portfolio. In this article we propose such a measure ("linguistic quotient" - LQ) that can account for these effects. We define the properties that such a measure should have. They are based on the idea of coherent risk measures from the mathematical finance. Having laid down the foundation, we propose one such a measure together with the algorithm that works on languages classification tree as input. The algorithm together with the input is available online at lingvometer.com