5,965 research outputs found
An Abstract Machine for Unification Grammars
This work describes the design and implementation of an abstract machine,
Amalia, for the linguistic formalism ALE, which is based on typed feature
structures. This formalism is one of the most widely accepted in computational
linguistics and has been used for designing grammars in various linguistic
theories, most notably HPSG. Amalia is composed of data structures and a set of
instructions, augmented by a compiler from the grammatical formalism to the
abstract instructions, and a (portable) interpreter of the abstract
instructions. The effect of each instruction is defined using a low-level
language that can be executed on ordinary hardware.
The advantages of the abstract machine approach are twofold. From a
theoretical point of view, the abstract machine gives a well-defined
operational semantics to the grammatical formalism. This ensures that grammars
specified using our system are endowed with well defined meaning. It enables,
for example, to formally verify the correctness of a compiler for HPSG, given
an independent definition. From a practical point of view, Amalia is the first
system that employs a direct compilation scheme for unification grammars that
are based on typed feature structures. The use of amalia results in a much
improved performance over existing systems.
In order to test the machine on a realistic application, we have developed a
small-scale, HPSG-based grammar for a fragment of the Hebrew language, using
Amalia as the development platform. This is the first application of HPSG to a
Semitic language.Comment: Doctoral Thesis, 96 pages, many postscript figures, uses pstricks,
pst-node, psfig, fullname and a macros fil
Building a robust dialogue system with limited data
We describe robustness techniques used in the CommandTalk system at the recognition level, the parsing level, and th dia6ue level, and how these were influenced by the lack of domain data. We used interviews with subject matter experts (SME's) to develop a single grammar for recognition, understanding, and generation, thus eliminating the need for a robust parser. We broadened the coverage of the recognition grammar by allowing word insertions and deletions, and we implemented clarification and correction subdialogues to increase robustness at tte dialogue level. We discuss the applicability of these techniques to other domains
Apportioning Development Effort in a Probabilistic LR Parsing System through Evaluation
We describe an implemented system for robust domain-independent syntactic
parsing of English, using a unification-based grammar of part-of-speech and
punctuation labels coupled with a probabilistic LR parser. We present
evaluations of the system's performance along several different dimensions;
these enable us to assess the contribution that each individual part is making
to the success of the system as a whole, and thus prioritise the effort to be
devoted to its further enhancement. Currently, the system is able to parse
around 80% of sentences in a substantial corpus of general text containing a
number of distinct genres. On a random sample of 250 such sentences the system
has a mean crossing bracket rate of 0.71 and recall and precision of 83% and
84% respectively when evaluated against manually-disambiguated analyses.Comment: 10 pages, 1 Postscript figure. To Appear in Proceedings of the
Conference on Empirical Methods in Natural Language Processing, University of
Pennsylvania, May 199
A Variant of Earley Parsing
The Earley algorithm is a widely used parsing method in natural language
processing applications. We introduce a variant of Earley parsing that is based
on a ``delayed'' recognition of constituents. This allows us to start the
recognition of a constituent only in cases in which all of its subconstituents
have been found within the input string. This is particularly advantageous in
several cases in which partial analysis of a constituent cannot be completed
and in general in all cases of productions sharing some suffix of their
right-hand sides (even for different left-hand side nonterminals). Although the
two algorithms result in the same asymptotic time and space complexity, from a
practical perspective our algorithm improves the time and space requirements of
the original method, as shown by reported experimental results.Comment: 12 pages, 1 Postscript figure, uses psfig.tex and llncs.st
Hybrid language processing in the Spoken Language Translator
The paper presents an overview of the Spoken Language Translator (SLT)
system's hybrid language-processing architecture, focussing on the way in which
rule-based and statistical methods are combined to achieve robust and efficient
performance within a linguistically motivated framework. In general, we argue
that rules are desirable in order to encode domain-independent linguistic
constraints and achieve high-quality grammatical output, while corpus-derived
statistics are needed if systems are to be efficient and robust; further, that
hybrid architectures are superior from the point of view of portability to
architectures which only make use of one type of information. We address the
topics of ``multi-engine'' strategies for robust translation; robust bottom-up
parsing using pruning and grammar specialization; rational development of
linguistic rule-sets using balanced domain corpora; and efficient supervised
training by interactive disambiguation. All work described is fully implemented
in the current version of the SLT-2 system.Comment: 4 pages, uses icassp97.sty; to appear in ICASSP-97; see
http://www.cam.sri.com for related materia
Parsing of Spoken Language under Time Constraints
Spoken language applications in natural dialogue settings place serious
requirements on the choice of processing architecture. Especially under adverse
phonetic and acoustic conditions parsing procedures have to be developed which
do not only analyse the incoming speech in a time-synchroneous and incremental
manner, but which are able to schedule their resources according to the varying
conditions of the recognition process. Depending on the actual degree of local
ambiguity the parser has to select among the available constraints in order to
narrow down the search space with as little effort as possible.
A parsing approach based on constraint satisfaction techniques is discussed.
It provides important characteristics of the desired real-time behaviour and
attempts to mimic some of the attention focussing capabilities of the human
speech comprehension mechanism.Comment: 19 pages, LaTe
An Efficient Implementation of the Head-Corner Parser
This paper describes an efficient and robust implementation of a
bi-directional, head-driven parser for constraint-based grammars. This parser
is developed for the OVIS system: a Dutch spoken dialogue system in which
information about public transport can be obtained by telephone.
After a review of the motivation for head-driven parsing strategies, and
head-corner parsing in particular, a non-deterministic version of the
head-corner parser is presented. A memoization technique is applied to obtain a
fast parser. A goal-weakening technique is introduced which greatly improves
average case efficiency, both in terms of speed and space requirements.
I argue in favor of such a memoization strategy with goal-weakening in
comparison with ordinary chart-parsers because such a strategy can be applied
selectively and therefore enormously reduces the space requirements of the
parser, while no practical loss in time-efficiency is observed. On the
contrary, experiments are described in which head-corner and left-corner
parsers implemented with selective memoization and goal weakening outperform
`standard' chart parsers. The experiments include the grammar of the OVIS
system and the Alvey NL Tools grammar.
Head-corner parsing is a mix of bottom-up and top-down processing. Certain
approaches towards robust parsing require purely bottom-up processing.
Therefore, it seems that head-corner parsing is unsuitable for such robust
parsing techniques. However, it is shown how underspecification (which arises
very naturally in a logic programming environment) can be used in the
head-corner parser to allow such robust parsing techniques. A particular robust
parsing model is described which is implemented in OVIS.Comment: 31 pages, uses cl.st
Efficient Tabular LR Parsing
We give a new treatment of tabular LR parsing, which is an alternative to
Tomita's generalized LR algorithm. The advantage is twofold. Firstly, our
treatment is conceptually more attractive because it uses simpler concepts,
such as grammar transformations and standard tabulation techniques also know as
chart parsing. Secondly, the static and dynamic complexity of parsing, both in
space and time, is significantly reduced.Comment: 8 pages, uses aclap.st
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