In this work, Morfessor, a morpheme segmentation model and algorithm developed by the organizers of the Morpho Challenge, is outlined and references are made to earlier work. Although Morfessor does not take part in the official Challenge competition, we report experimental results for the morpheme segmentation of English, Finnish and Turkish words. The obtained results are very good. Morfessor outperforms the other algorithms in the Finnish and Turkish tasks and comes second in the English task. In the Finnish speech recognition task, Morfessor achieves the lowest letter error rate.
Our algorithm, ParaMor, fared well in Morpho Challenge 2007 (Kurimo et al., 2007), a peer operated c...
Data-driven segmentation of words into subword units has been used in various natural language proce...
Abstract. We extend the unsupervised morpheme segmentation method Morfessor Baseline to account for ...
In the Morpho Challenge 2009 unsupervised algorithms that provide morpheme anal-yses for words in di...
ParaMor, our unsupervised morphology induction system performed well at Morpho Challenge 2008. When ...
In natural language processing many practical tasks, such as speech recognition, information retriev...
In order to develop computer applications that successfully process natural language data (text and ...
| openaire: EC/H2020/771113/EU//FoTranIn our submission to the SIGMORPHON 2022 Shared Task on Morphe...
ParaMor, our unsupervised morphology in-duction algorithm placed well in Morpho Challenge 2007 (Kuri...
We present two methods for unsupervised segmentation of words into morpheme-like units. The model ut...
We present a simple algorithm that is also psychologically plausible to perform un-supervised learni...
Morfessor is a family of methods for learning morphological segmentations of words based on unannota...
We present two methods for unsupervised segmentation of words into morpheme-like units. The model ...
This document describes Hutmegs, the Helsinki University of Technology Morphological Evaluation Gold...
Machine learning methods are increasingly applied to automated processing of natural language data. ...
Our algorithm, ParaMor, fared well in Morpho Challenge 2007 (Kurimo et al., 2007), a peer operated c...
Data-driven segmentation of words into subword units has been used in various natural language proce...
Abstract. We extend the unsupervised morpheme segmentation method Morfessor Baseline to account for ...
In the Morpho Challenge 2009 unsupervised algorithms that provide morpheme anal-yses for words in di...
ParaMor, our unsupervised morphology induction system performed well at Morpho Challenge 2008. When ...
In natural language processing many practical tasks, such as speech recognition, information retriev...
In order to develop computer applications that successfully process natural language data (text and ...
| openaire: EC/H2020/771113/EU//FoTranIn our submission to the SIGMORPHON 2022 Shared Task on Morphe...
ParaMor, our unsupervised morphology in-duction algorithm placed well in Morpho Challenge 2007 (Kuri...
We present two methods for unsupervised segmentation of words into morpheme-like units. The model ut...
We present a simple algorithm that is also psychologically plausible to perform un-supervised learni...
Morfessor is a family of methods for learning morphological segmentations of words based on unannota...
We present two methods for unsupervised segmentation of words into morpheme-like units. The model ...
This document describes Hutmegs, the Helsinki University of Technology Morphological Evaluation Gold...
Machine learning methods are increasingly applied to automated processing of natural language data. ...
Our algorithm, ParaMor, fared well in Morpho Challenge 2007 (Kurimo et al., 2007), a peer operated c...
Data-driven segmentation of words into subword units has been used in various natural language proce...
Abstract. We extend the unsupervised morpheme segmentation method Morfessor Baseline to account for ...