New Measure of Language Complexity Based on Hierarchical Pattern Reuse
Researchers introduced the ladderpath index, a new computational measure of language complexity based on how efficiently languages can be reconstructed through hierarchical reuse of repeated substructures. Testing across 21 languages from the Parallel Universal Dependencies dataset, they found that languages maintain approximately equal overall complexity despite differences in corpus length and character inventory size. The findings support the equi-complexity hypothesis and suggest that linguistic complexity is conserved but redistributed across different linguistic levels, with implications for understanding both language structure and human cognitive processing.
A new study proposes the ladderpath index as a measure of language complexity grounded in algorithmic information theory, which counts the minimum steps needed to reconstruct linguistic sequences through hierarchical reuse of repeated substructures. Applied to 21 parallel corpora, the measure shows that languages maintain approximately invariant complexity levels across different writing systems and corpus sizes, with complexity varying much less than corpus length itself. The research identifies trade-offs between character inventory size and corpus length, and between vocabulary-level and corpus-level reconstruction complexity, supporting the hypothesis that total linguistic complexity is conserved but redistributed across different linguistic levels. Notably, the substructures identified by the algorithmic approach—without any linguistic input—overlap with actual words and morphological components in natural languages. The authors connect their findings to cognitive science theories of chunking, proposing that the hierarchmic reuse patterns captured by the ladderpath approach parallel how human cognitive systems compress linguistic input into nested, reusable units under memory and processing constraints.
What's missing
The study's own limitations and open questions are not detailed in the abstract provided, such as: whether the findings generalize to languages with significantly different typological features not represented in the dataset, the computational scalability of the ladderpath approach to larger corpora, or how the measure performs on languages with different writing systems beyond the binary representation tested.
What different sources said
- arXiv cs.CLCenter
Measuring language complexity from hierarchical reuse of recurring patterns
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