Corpus ID: 2666779

The Study of Effect of Length in Morphological Segmentation of Agglutinative Languages

@inproceedings{Ramasamy2012TheSO,
  title={The Study of Effect of Length in Morphological Segmentation of Agglutinative Languages},
  author={L. Ramasamy and Z. Žabokrtsk{\'y} and Sowmya Vajjala},
  year={2012}
}
Morph length is one of the indicative feature that helps learning the morphology of languages, in particular agglutinative languages. In this paper, we introduce a simple unsupervised model for morphological segmentation and study how the knowledge of morph length affect the performance of the segmentation task under the Bayesian framework. The model is based on (Goldwater et al., 2006) unigram word segmentation model and assumes a simple prior distribution over morph length. We experiment this… Expand
Ascertaining the morphological components of Tamil language using unsupervised approach
CLARA: A New Generation of Researchers in Common Language Resources and Their Applications
Unsupervised and Semi-Supervised Multilingual Learning for Resource-Poor Languages

References

SHOWING 1-10 OF 27 REFERENCES
Unsupervised Learning of the Morphology of a Natural Language
High-Performance, Language-Independent Morphological Segmentation
Unsupervised Segmentation of Words Using Prior Distributions of Morph Length and Frequency
Unsupervised Multilingual Learning for Morphological Segmentation
A TELUGU MORPHOLOGICAL ANALYZER
Improving morphology induction by learning spelling rules
A Language-Independent Unsupervised Model for Morphological Segmentation
...
1
2
3
...