Porting Basque Morphological Grammars to foma, an Open-Source Tool

Alegria, Iñaki; Etxeberría, Igone; Hulden, Mans; Maritxalar, Montserrat

doi:10.1007/978-3-642-14684-8_11

Cited by 5 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…6 Novel data for Haida, a severely endangered North American language isolate, was prepared by Jordan Lachler (University of Alberta). The Basque language data was extracted from a manually designed finite-state morphological analyzer (Alegria et al, 2009).…”

Section: Languagesmentioning

confidence: 99%

CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages

Cotterell¹,

Kirov²,

Sylak-Glassman³

et al. 2017

Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection

Self Cite

162

151

View full text Add to dashboard Cite

The CoNLL-SIGMORPHON 2017 shared task on supervised morphological generation required systems to be trained and tested in each of 52 typologically diverse languages. In sub-task 1, submitted systems were asked to predict a specific inflected form of a given lemma. In sub-task 2, systems were given a lemma and some of its specific inflected forms, and asked to complete the inflectional paradigm by predicting all of the remaining inflected forms. Both sub-tasks included high, medium, and low-resource conditions. Sub-task 1 received 24 system submissions, while sub-task 2 received 3 system submissions. Following the success of neural sequence-to-sequence models in the SIGMORPHON 2016 shared task, all but one of the submissions included a neural component. The results show that high performance can be achieved with small training datasets, so long as models have appropriate inductive bias or make use of additional unlabeled data or synthetic data. However, different biasing and data augmentation resulted in non-identical sets of inflected forms being predicted correctly, suggesting that there is room for future improvement.

show abstract

Section: Languagesmentioning

confidence: 99%

CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages

Cotterell¹,

Kirov²,

Sylak-Glassman³

et al. 2017

Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection

Self Cite

162

151

View full text Add to dashboard Cite

show abstract

“…• For selecting standard words in Basque, a morphological analyzer of Basque was used (Alegria et al 2009). • For Spanish, the FreeLing suite (Carreras et al 2004) was used for filtering the proposals.…”

Section: The Wfst-based Methodsmentioning

confidence: 99%

“…The randomly selected parts of the corpus were analyzed by a morphological analyzer of standard Basque (Alegria et al 2009). This way, words to be set aside for manual checking, that is, OOV items, with regard to the Basque, morphological analyzer were detected and after annotating these, a small parallel corpus was built.…”

Section: Basque Historical Corpusmentioning

confidence: 99%

Weighted finite-state transducers for normalization of historical texts

2019

Self Cite

View full text Add to dashboard Cite

This paper presents a study about methods for normalization of historical texts. The aim of these methods is learning relations between historical and contemporary word forms. We have compiled training and test corpora for different languages and scenarios, and we have tried to read the results related to the features of the corpora and languages. Our proposed method, based on weighted finite-state transducers, is compared to previously published ones. Our method learns to map phonological changes using a noisy channel model; it is a simple solution that can use a limited amount of supervision in order to achieve adequate performance. The compiled corpora are ready to be used for other researchers in order to compare results. Concerning the amount of supervision for the task, we investigate how the size of training corpus affects the results and identify some interesting factors to anticipate the difficulty of the task.

show abstract

“…Similar efforts has taken place for another Algonquian language, Plains Cree (Snoek et al, 2014). Having developed a finite-state morphological parser for a morphologically complex language, developing a spell checker (or even corrector), a lemmatizer, or e-dictionary tools would be more accessible for any language (Alegria et al, 2009;Pirinen and Hardwick, 2012). This is much more crucial for languages with a heavy use of morphology, such as the Algonquian languages.…”

Section: Creating Computer Resources For Arapaho 31 Morphological Pamentioning

confidence: 99%

Creating lexical resources for polysynthetic languages–-the case of Arapaho

Kazeminejad¹,

Cowell²,

Hulden³

2017

Proceedings of the 2nd Workshop on the Use of Computational Methods in the Study of Endangered Languages

Self Cite

View full text Add to dashboard Cite

This paper discusses the challenges in creating pedagogical and research resources for the Arapaho language. Because of the complex morphology of this language, printed resources cannot provide the typical useful functions that they can for many other languages. We discuss the challenges faced by most learners and researchers working with polysynthetic languages, of which Arapaho is an excellent example, as well as some currently implemented solutions in creating computer resources for this language, including a lexical database, a morphological parser, and a concordancer. The construction of the finite-state morphological parser which many downstream tasks rely on will be discussed in some detail.

show abstract

Porting Basque Morphological Grammars to foma, an Open-Source Tool

Cited by 5 publications

References 4 publications

CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages

CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages

Weighted finite-state transducers for normalization of historical texts

Creating lexical resources for polysynthetic languages–-the case of Arapaho

Contact Info

Product

Resources

About