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Unsupervised models for morpheme segmentation and morphology learning
Mathias Creutz, Krista Lagus, 2007. ACM Transactions on Speech and Language Processing.
Presents Morfessor, a family of probabilistic models that learn to split words into morph-like segments from raw text, evaluated on Finnish and English.
What it's used for here
The linguistics and inductive-methods surveys list Morfessor among morphology-induction methods not yet applied to the Voynich text.
Cited by on this site 4 records
4 methods surveys
SRCSignal processing, mathematics, linguistics, inductive methods
Cite it
Creutz, M., & Lagus, K. (2007). Unsupervised models for morpheme segmentation and morphology learning. ACM Transactions on Speech and Language Processing. https://doi.org/10.1145/1187415.1187418
@article{creutz2007unsupervised,
author = {Creutz, Mathias and Lagus, Krista},
title = {Unsupervised models for morpheme segmentation and morphology learning},
journal = {ACM Transactions on Speech and Language Processing},
year = {2007},
doi = {10.1145/1187415.1187418},
url = {https://doi.org/10.1145/1187415.1187418}
}TY - JOUR TI - Unsupervised models for morpheme segmentation and morphology learning AU - Creutz, Mathias AU - Lagus, Krista PY - 2007 JO - ACM Transactions on Speech and Language Processing DO - 10.1145/1187415.1187418 UR - https://doi.org/10.1145/1187415.1187418 ER -
Creutz, Mathias and Krista Lagus. “Unsupervised models for morpheme segmentation and morphology learning.” ACM Transactions on Speech and Language Processing (2007). https://doi.org/10.1145/1187415.1187418.