CLPRDATA-ANJul 25, 2013

Information content versus word length in natural language: A reply to Ferrer-i-Cancho and Moscoso del Prado Martin [arXiv:1209.1751]

arXiv:1307.6726v18 citations
Originality Synthesis-oriented
AI Analysis

This addresses a debate in linguistics about language efficiency, but it is incremental as it primarily refutes existing claims without introducing new data or methods.

The authors critique a prior study that argued against communicative efficiency in human language based on word length and surprisal, highlighting flaws in the model's assumptions and its failure to explain language patterns and behavioral results.

Recently, Ferrer i Cancho and Moscoso del Prado Martin [arXiv:1209.1751] argued that an observed linear relationship between word length and average surprisal (Piantadosi, Tily, & Gibson, 2011) is not evidence for communicative efficiency in human language. We discuss several shortcomings of their approach and critique: their model critically rests on inaccurate assumptions, is incapable of explaining key surprisal patterns in language, and is incompatible with recent behavioral results. More generally, we argue that statistical models must not critically rely on assumptions that are incompatible with the real system under study.

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