Departamento de Lenguajes y Sistemas Informáticos


Título:RECORDATORI: About Hierarchical, Syntax-Enriched Machine Translation Incorpóralo a tu calendario:
Por:Prof. Khalil Sima'an, Universiteit van Amsterdam
Lugar:Sala Claude Shannon, soterrani, Edifici Politècnica IV
Día/hora:14/11/2011 12:00
Duración aproximada:1:30 horas
Persona de contacto:Forcada Zubizarreta, Mikel L. (mlf[Perdone'm]
Over the past years, there have been various efforts
at incorporating monolingual syntax into statistical
machine translation. The main difficulty often seems that
translation equivalence does not necessarily conform to
monolingual syntactic constituency structure, as assumed
by traditional compositional semantics. In this talk I
will reflect on the origins of syntactic structure to
show that the information represented in a syntactic tree
can be represented in alternative ways. By representing
this information adequately, syntactic information can be
brought into statistical MT models effectively. In will
give a bird's-eye view of three recent models developed
together with my co-workers and touch upon some relevant
aspects. After that I will discuss the reverse problem of
how to represent word alignments hierarchically in order
to capture the relations of translation equivalence
adequately. By doing so, our aim is to use this new
hierarchical representation to pave the way for learning
compositional statistical synchronous grammars from
word-aligned parallel corpora. This is ongoing work with
the fundamental results currently in submission.
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