Daniel Quernheim

Learn More
Minimal deterministic finite automata (dfas) can be reduced further at the expense of a finite number of errors. Recently, such minimization algorithms have been improved to run in time O(n logn), where n is the number of states of the input dfa, by [Gawrychowski and Jeż: Hyper-minimisation made efficient. Proc. Mfcs, Lncs 5734, 2009] and [Holzer and(More)
Weighted finite-state acceptors and transducers (Pereira and Riley, 1997) are a critical technology for NLP and speech systems. They flexibly capture many kinds of stateful left-toright substitution, simple transducers can be composed into more complex ones, and they are EMtrainable. They are unable to handle long-range syntactic movement, but tree(More)
We present a new translation model integrating the shallow local multi bottomup tree transducer. We perform a largescale empirical evaluation of our obtained system, which demonstrates that we significantly beat a realistic tree-to-tree baseline on the WMT 2009 English→German translation task. As an additional contribution we make the developed software and(More)
Hyper-minimisation of deterministic nite automata is a recently introduced state reduction technique that allows a nite change in the recognised language. A generalisation of this lossy compression method to the weighted setting over semi elds is presented, which allows the recognised formal power series to di er for nitely many input strings. First, the(More)
Hyper-minimization of deterministic nite automata (dfa) is a recently introduced state reduction technique that allows a nite change in the recognized language. A generalization of this lossy compression method to the weighted setting over semi elds is presented, which allows the recognized weighted language to di er for nitely many input strings. First,(More)
We present an experimental statistical tree-to-tree machine translation system based on the multi-bottom up tree transducer including rule extraction, tuning and decoding. Thanks to input parse forests and a “no pruning” strategy during decoding, the obtained translations are competitive. The drawbacks are a restricted coverage of 70% on test data, in part(More)
An open question in [FÜLÖP, MALETTI, VOGLER: Weighted extended tree transducers. Fundamenta Informaticae 111(2), 2011] asks whether weighted linear extended tree transducers preserve recognizability in countably complete commutative semirings. In this contribution, the question is answered positively, which is achieved with a construction that utilizes(More)