20 research outputs found
Inquiries into words, constraints and contexts : Festschrift in the honour of Kimmo Koskenniemi on his 60th birthday
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Probabilistic Modelling of Morphologically Rich Languages
Full text linkThis thesis investigates how the sub-structure of words can be accounted for
in probabilistic models of language. Such models play an important role in
natural language processing tasks such as translation or speech recognition,
but often rely on the simplistic assumption that words are opaque symbols. This
assumption does not fit morphologically complex language well, where words can
have rich internal structure and sub-word elements are shared across distinct
word forms.
Our approach is to encode basic notions of morphology into the assumptions of
three different types of language models, with the intention that leveraging
shared sub-word structure can improve model performance and help overcome data
sparsity that arises from morphological processes.
In the context of n-gram language modelling, we formulate a new Bayesian
model that relies on the decomposition of compound words to attain better
smoothing, and we develop a new distributed language model that learns vector
representations of morphemes and leverages them to link together
morphologically related words. In both cases, we show that accounting for word
sub-structure improves the models' intrinsic performance and provides benefits
when applied to other tasks, including machine translation.
We then shift the focus beyond the modelling of word sequences and consider
models that automatically learn what the sub-word elements of a given language
are, given an unannotated list of words. We formulate a novel model that can
learn discontiguous morphemes in addition to the more conventional contiguous
morphemes that most previous models are limited to. This approach is
demonstrated on Semitic languages, and we find that modelling discontiguous
sub-word structures leads to improvements in the task of segmenting words into
their contiguous morphemes.Comment: DPhil thesis, University of Oxford, submitted and accepted 2014.
http://ora.ox.ac.uk/objects/uuid:8df7324f-d3b8-47a1-8b0b-3a6feb5f45c
CLARIN
Get PDFThe book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium
CLARIN. The infrastructure for language resources
Get PDFCLARIN, the "Common Language Resources and Technology Infrastructure", has established itself as a major player in the field of research infrastructures for the humanities. This volume provides a comprehensive overview of the organization, its members, its goals and its functioning, as well as of the tools and resources hosted by the infrastructure. The many contributors representing various fields, from computer science to law to psychology, analyse a wide range of topics, such as the technology behind the CLARIN infrastructure, the use of CLARIN resources in diverse research projects, the achievements of selected national CLARIN consortia, and the challenges that CLARIN has faced and will face in the future.
The book will be published in 2022, 10 years after the establishment of CLARIN as a European Research Infrastructure Consortium by the European Commission (Decision 2012/136/EU)
CLARIN
Get PDFThe book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium
