CLMar 20, 2015

On measuring linguistic intelligence

arXiv:1503.06151v1
Originality Synthesis-oriented
AI Analysis

This addresses the need for a standardized metric to assess linguistic intelligence, particularly for multilingual individuals, though it is incremental as it adapts existing financial concepts to a new domain.

The paper tackles the problem of assigning a meaningful score to a person's language portfolio by accounting for language similarity and proficiency levels, proposing a 'linguistic quotient' (LQ) measure based on coherent risk measures from mathematical finance.

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

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