Morpheme Induction for Emergent Language

ACL ARR 2025 May Submission4180 Authors

Abstract: We introduce CSAR, an algorithm for inducing morphemes from emergent language corpora of parallel utterances and meanings. It is a greedy algorithm which (1) weights morphemes based on mutual information between forms and meanings, (2) selects the highest-weighted pair, (3) removes it from the corpus, and (4) repeats the process to induce further morphemes (i.e., Count, Select, Ablate, Repeat). The effectiveness of CSAR is first validated on procedurally generated datasets and compared against baselines for related tasks. Second, we validate CSAR's performance on human language data to show that the algorithm makes reasonable predictions in adjacent domains. Finally, we analyze a handful of emergent languages, quantifying linguistic characteristics like degree of synonymy and polysemy.

Paper Type: Long

Research Area: Phonology, Morphology and Word Segmentation

Research Area Keywords: morphological segmentation

Contribution Types: Model analysis & interpretability, Publicly available software and/or pre-trained models

Languages Studied: English, German, emergent languages, synthetic languages

Submission Number: 4180