9 research outputs found
Unifying synchronous tree-adjoining grammars and tree transducers via bimorphisms.
We place synchronous tree-adjoining grammars and tree transducers in the single overarching framework of bimorphisms, continuing the unification of synchronous grammars and tree transducers initiated by Shieber (2004). Along the way, we present a new definition of the tree-adjoining grammar derivation relation based on a novel direct inter-reduction of TAG and monadic macro tree transducers.Engineering and Applied Science
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Synchronous grammars as tree transducers
Tree transducer formalisms were developed in the formal language theory community as generalizations of finite-state transducers from strings to trees. Independently, synchronous tree-substitution and -adjoining grammars arose in the computational linguistics community as a means to augment strictly syntactic formalisms to provide for parallel semantics. We present the first synthesis of these two independently developed approaches to specifying tree relations, unifying their respective literatures for the first time, by using the framework of bimorphisms as the generalizing formalism in which all can be embedded. The central result is that synchronous tree-substitution grammars are equivalent to bimorphisms where the component homomorphisms are linear and complete.Engineering and Applied Science
Bimorphisms and synchronous grammars
We tend to think of the study of language as proceeding by characterizing the strings and structures of a language, and we think of natural language processing as using those structures to build systems of utility in manipulating the language. But many language-related problems are more fruitfully viewed as requiring the specification of a relation between two languages, rather than the specification of a single language. We provide a synthesis and extension of work that unifies two approaches to such language relations: the automata-theoretic approach based on tree transducers that transform trees to their counterparts in the relation, and the grammatical approach based on synchronous grammars that derive pairs of trees in the relation. In particular, we characterize synchronous tree-substitution grammars and synchronous tree-adjoining grammars in terms of bimorphisms, which have previously been used to characterize tree transducers. In the process, we provide new approaches to formalizing the various concepts: a metanotation for describing varieties of tree automata and transducers in equational terms; a rigorous formalization of tree-adjoining and tree-substitution grammars and their synchronous counterparts, using trees over ranked alphabets; and generalizations of tree-adjoining grammar allowing multiple adjunction.Engineering and Applied Science
Feature Unification in TAG Derivation Trees
The derivation trees of a tree adjoining grammar provide a first insight into
the sentence semantics, and are thus prime targets for generation systems. We
define a formalism, feature-based regular tree grammars, and a translation from
feature based tree adjoining grammars into this new formalism. The translation
preserves the derivation structures of the original grammar, and accounts for
feature unification.Comment: 12 pages, 4 figures In TAG+9, Ninth International Workshop on Tree
Adjoining Grammars and Related Formalisms, 200
Using Regular Tree Grammars to enhance Sentence Realisation
International audienceFeature-based regular tree grammars (FRTG) can be used to generate the derivation trees of a feature-based tree adjoining grammar (FTAG). We make use of this fact to specify and implement both an FTAG-based sentence realiser and a benchmark generator for this realiser. We argue furthermore that the FRTG encoding enables us to improve on other proposals based on a grammar of TAG derivation trees in several ways. It preserves the compositional semantics that can be encoded in feature-based TAGs; it increases efficiency and restricts overgeneration; and it provides a uniform resource for generation, benchmark construction, and parsing
New Results on Context-Free Tree Languages
Context-free tree languages play an important role in algebraic semantics and are applied in mathematical linguistics. In this thesis, we present some new results on context-free tree languages
A prototype system for machine translation from English to South African Sign Language using synchronous tree adjoining grammars
Thesis (MSc)--University of Stellenbosch, 2007.ENGLISH ABSTRACT: Machine translation, especially machine translation for sign languages, remains an active research
area. Sign language machine translation presents unique challenges to the whole machine translation
process. In this thesis a prototype machine translation system is presented. This system is
designed to translate English text into a gloss based representation of South African Sign Language
(SASL).
In order to perform the machine translation, a transfer based approach was taken. English
text is parsed into an intermediate representation. Translation rules are then applied to this
intermediate representation to transform it into an equivalent intermediate representation for the
SASL glosses. For both these intermediate representations, a tree adjoining grammar (TAG)
formalism is used. As part of the prototype machine translation system, a TAG parser was
implemented.
The translation rules used by the system were derived from a SASL phrase book. This phrase
book was also used to create a small gloss based SASL TAG grammar. Lastly, some additional
tools, for the editing of TAG trees, were also added to the prototype system.AFRIKAANSE OPSOMMING: Masjienvertaling, veral masjienvertaling vir gebaretale, bly ’n aktiewe navorsingsgebied. Masjienvertaling
vir gebaretale bied unieke uitdagings tot die hele masjienvertalingproses. In hierdie tesis
bied ons ’n prototipe masjienvertalingstelsel aan. Hierdie stelsel is ontwerp om Engelse teks te
vertaal na ’n glos gebaseerde voorstelling van Suid-Afrikaanse Gebaretaal (SAG).
Ons vertalingstelsel maak gebruik van ’n oorplasingsbenadering tot masjienvertaling. Engelse
teks word ontleed na ’n intermediˆere vorm. Vertalingre¨els word toegepas op hierdie intermediˆere
vorm om dit te transformeer na ’n ekwivalente intermediˆere vorm vir die SAG glosse. Vir beide
hierdie intermediˆere vorms word boomkoppelingsgrammatikas (BKGs) gebruik. As deel van die
prototipe masjienvertalingstelsel, is ’n BKG sintaksontleder ge¨ımplementeer.
Die vertalingre¨els wat gebruik word deur die stelsel, is afgelei vanaf ’n SAG fraseboek. Hierdie
fraseboek was ook gebruik om ’n klein BKG vir SAG glosse te ontwikkel. Laastens was addisionele
nutsfasiliteite, vir die redigering van BKG bome, ontwikkel
Learning words and syntactic cues in highly ambiguous contexts
The cross-situational word learning paradigm argues that word meanings can be approximated
by word-object associations, computed from co-occurrence statistics between
words and entities in the world. Lexicon acquisition involves simultaneously
guessing (1) which objects are being talked about (the ”meaning”) and (2) which words
relate to those objects. However, most modeling work focuses on acquiring meanings
for isolated words, largely neglecting relationships between words or physical entities,
which can play an important role in learning.
Semantic parsing, on the other hand, aims to learn a mapping between entire utterances
and compositional meaning representations where such relations are central.
The focus is the mapping between meaning and words, while utterance meanings are
treated as observed quantities.
Here, we extend the joint inference problem of word learning to account for compositional
meanings by incorporating a semantic parsing model for relating utterances
to non-linguistic context. Integrating semantic parsing and word learning permits us to
explore the impact of word-word and concept-concept relations.
The result is a joint-inference problem inherited from the word learning setting
where we must simultaneously learn utterance-level and individual word meanings,
only now we also contend with the many possible relationships between concepts in
the meaning and words in the sentence. To simplify design, we factorize the model into
separate modules, one for each of the world, the meaning, and the words, and merge
them into a single synchronous grammar for joint inference.
There are three main contributions. First, we introduce a novel word learning
model and accompanying semantic parser. Second, we produce a corpus which allows
us to demonstrate the importance of structure in word learning. Finally, we also
present a number of technical innovations required for implementing such a model
Weighted Tree Automata -- May it be a little more?
This is a book on weighted tree automata. We present the basic definitions
and some of the important results in a coherent form with full proofs. The
concept of weighted tree automata is part of Automata Theory and it touches the
area of Universal Algebra. It originated from two sources: weighted string
automata and finite-state tree automata