Ramon Granell

Also published as: Ramón Granell


2018

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On Hapax Legomena and Morphological Productivity
Janet Pierrehumbert | Ramon Granell
Proceedings of the Fifteenth Workshop on Computational Research in Phonetics, Phonology, and Morphology

Quantifying and predicting morphological productivity is a long-standing challenge in corpus linguistics and psycholinguistics. The same challenge reappears in natural language processing in the context of handling words that were not seen in the training set (out-of-vocabulary, or OOV, words). Prior research showed that a good indicator of the productivity of a morpheme is the number of words involving it that occur exactly once (the hapax legomena). A technical connection was adduced between this result and Good-Turing smoothing, which assigns probability mass to unseen events on the basis of the simplifying assumption that word frequencies are stationary. In a large-scale study of 133 affixes in Wikipedia, we develop evidence that success in fact depends on tapping the frequency range in which the assumptions of Good-Turing are violated.

2009

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Simultaneous Dialogue Act Segmentation and Labelling using Lexical and Syntactic Features
Ramon Granell | Stephen Pulman | Carlos-D. Martínez-Hinarejos
Proceedings of the SIGDIAL 2009 Conference

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Unsupervised Classification of Dialogue Acts using a Dirichlet Process Mixture Model
Nigel Crook | Ramon Granell | Stephen Pulman
Proceedings of the SIGDIAL 2009 Conference

2006

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Segmented and Unsegmented Dialogue-Act Annotation with Statistical Dialogue Models
Carlos D. Martínez Hinarejos | Ramón Granell | José Miguel Benedí
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions