Fast Computation of Normalized Edit Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Acquiring receptive morphology: a connectionist model
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
SEMHE: a generalised two-level system
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Machine learning of morphological rules by generalization and analogy
COLING '86 Proceedings of the 11th coference on Computational linguistics
Unsupervised discovery of phonological categories through supervised learning of morphological rules
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Learning morphology: algorithms for the identification of the stem changes
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Automatic Acquisition of Morphological Knowledge for Medical Language Processing
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Bootstrapping morphological analyzers by combining human elicitation and machine learning
Computational Linguistics
Minimally supervised morphological analysis by multimodal alignment
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Accenting unknown words in a specialized language
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
Generating the translation equivalent of agentive nouns using two-level morphology
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Research on Language and Computation
Semi-automatic acquisition of two-level morphological rules for iban language
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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We describe and experimentally evaluate a complete method for the automatic acquisition of two-level rules for morphological analyzers/generators. The input to the system is sets of source-target word pairs, where the target is an inflected form of the source. There are two phases in the acquisition process: (1) segmentation of the target into morphemes and (2) determination of the optimal two-level rule set with minimal discerning contexts. In phase one, a minimal acyclic finite state automaton (AFSA) is constructed from string edit sequences of the input pairs. Segmentation of the words into morphemes is achieved through viewing the AFSA as a directed acyclic graph (DAG) and applying heuristics using properties of the DAG as well as the elementary edit operations. For phase two, the determination of the optimal rule set is made possible with a novel representation of rule contexts, with morpheme boundaries added, in a new DAG. We introduce the notion of a delimiter edge. Delimiter edges are used to select the correct two-level rule type as well as to extract minimal discerning rule contexts from the DAG. Results are presented for English adjectives, Xhosa noun locatives and Afrikaans noun plurals.