Unsupervised learning of agglutinated morphology using Nested Pitman-Yor Process based Morpheme Induction Algorithm

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10609/151505

Título :	Unsupervised learning of agglutinated morphology using Nested Pitman-Yor Process based Morpheme Induction Algorithm
Autoría:	Arun Kumar, Rajappan Nair Padró, Lluís Oliver, Antoni
Citación :	Kumar, A. [Mokhtar], Padró, L. [Lluís] & Oliver, A. [Antoni]. (2016). Unsupervised learning of agglutinated morphology using nested Pitman-Yor process based morpheme induction algorithm. A Y. Lu, W. Chen, M. Zhang, M. Dong & B. Ma (ed.). 2015 International Conference on Asian Language Processing (IALP) (p. 45-48). Los Alamitos, CA: IEEE Computer Society
Resumen :	In this paper we describe a method of morphologically segment highly agglutinating and inflectional languages from the Dravidian family. We use the nested Pitman-Yor process to segment long agglutinated words into their basic components, and use a corpus based morpheme induction algorithm to perform morpheme segmentation. We test our method on two languages, Malayalam and Kannada and compare the results with Morfessor-baseline.
Palabras clave :	Nested Pitman-Yor Process agglutinated morphology Indian languages
Tipo de documento:	info:eu-repo/semantics/conferenceObject
Fecha de publicación :	2015
Licencia de publicación:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Aparece en las colecciones:	Conferencias