Tree transducers, L systems, and two-way machines

A relationship between parallel rewriting systems and two-way machines is investigated. Restrictions on the “copying power” of these devices endow them with rich structuring and give insight into the issues of determinism, parallelism, and copying. Among the parallel rewriting systems considered are the top-down tree transducer; the generalized syntax-directed translation scheme and the ETOL system, and among the two-way machines are the tree-walking automaton, the two-way finite-state transducer, and (generalizations of) the one-way checking stack automaton. The. relationship of these devices to macro grammars is also considered. An effort is made .to provide a systematic survey of a number of existing results

Macro tree transducers

Macro tree transducers are a combination of top-down tree transducers and macro grammars. They serve as a model for syntax-directed semantics in which context information can be handled. In this paper the formal model of macro tree transducers is studied by investigating typical automata theoretical topics like composition, decomposition, domains, and ranges of the induced translation classes. The extension with regular look-ahead is considered

The Automatic Inversion of Attribute Grammars

Over the last decade there has developed an acute awareness of the need to introduce abstraction and mathematical rigor into the programming process. This increased formality allows for the automatic manipulation of software, increasing productivity and, even more importantly, the manageability of complex systems. Along these lines, attribute grammars constitute a formal mechanism (or specifying translations between languages; from a Cormal description of the translation a translator can be automatically constructed. In this paper we consider taking this process one step further: given an attribute grammar specifying the translation from language L1 to the language L2, we address the question of whether the inverse attribute grammar specifying the inverse translation from L2 to L1 can be automatically generated. We show how to solve this problem for a restricted subset of attribute grammars. This inversion process allows for compatible two-way translators to be generated from a single description. To show the practical feasibility of attribute grammar inversion, we relate our experience in inverting an attribute grammar used as an interface for a formal database accessing language, SQL. The attribute grammar is used to paraphrase SQL database queries in English

Translations on a context free grammar

Two schemes for the specification of translations on a context-free grammar are proposed. The first scheme, called a generalized syntax directed translation (GSDT), consists of a context free grammar with a set of semantic rules associated with each production of the grammar. In a GSDT an input word is parsed according to the underlying context free grammar, and at each node of the tree, a finite number of translation strings are computed in terms of the translation strings defined at the descendants of that node. The functional relationship between the length of input and length of output for translations defined by GSDT's is investigated.The second method for the specification of translations is in terms of tree automata—finite automata with output, walking on derivation trees of a context free grammar. It is shown that tree automata provide an exact characterization for those GSDT's with a linear relationship between input and output length

Elastic-substitution decoding for hierarchical SMT: efficiency, richer search and double labels

Elastic-substitution decoding (ESD), first introduced by Chiang (2010), can be important for obtaining good results when applying labels to enrich hierarchical statistical machine translation (SMT). However, an efficient implementation is essential for scalable application. We describe how to achieve this, contributing essential details that were missing in the original exposition. We compare ESD to strict matching and show its superiority for both reordering and syntactic labels. To overcome the sub-optimal performance due to the late evaluation of features marking label substitution types, we increase the diversity of the rules explored during cube pruning initialization with respect to labels their labels. This approach gives significant improvements over basic ESD and performs favorably compared to extending the search by increasing the cube pruning pop-limit. Finally, we look at combining multiple labels. The combination of reordering labels and target-side boundary-tags yields a significant improvement in terms of the word-order sensitive metrics Kendall reordering score and METEOR. This confirms our intuition that the combination of reordering labels and syntactic labels can yield improvements over either label by itself, despite increased sparsity