[From: http://www.iai.uni-sb.de/iaien/iaiwp/index.htm#content]
IAI
Working Paper No. 36
Hybrid
Approaches to Machine Translation
Oliver Streiter, Michael Carl, Johann Haller
(Editors)
Introduction
In order to offer a general
overview over current trends in Machine Translation, IAI, the Institute of Applied
Information Sciences, Saarbruecken,
Germany has
invited researchers to contribute to a collection of research papers related to
the topic of "Hybrid Approaches to Machine Translation". While the
70ties and 80ties have been dominated by the Rule-Based Approach to Machine
Translation (henceforth called RBMT), Corpus-Based approaches as Translation
Memories (TMs), Statistical
MT approaches (SBMT) and
Example-based approaches to MT have been proposed and developed in the early
90ties. Electronic dictionaries and termtools as a third type of translation
tools took off at the same time, as translators used the computer more and more
for their daily work.
Although the supporters of the RBMT approach came under pressure due to the
advantages the CBMT approaches have over RBMT, the first could find some
additional support in the newly developing web-based information technology,
such as multi-lingual information retrieval, on-line translation and
multi-lingual visualization. It thus became apparent that all approaches have
their individual strong and weak points, and that there are no ideal systems
unless specified for a narrowly defined translation setting. In addition, if
different approaches have different advantages they possibly can be combined
such as to produce more satisfying MT-systems.
The RBMT Approach
The RBMT approach is
introduced in this collection by a historical document entitled Linguistic and computational Motivations for the LOGOS
Machine Translation System. In this contribution, Scott restates the belief
of Rule-Based MT, that humans can develop an axiomatic representation for the
translation process through intense inflection.
Also the contribution “Reusability of wide coverage linguistic
resources in the construction of an English-Basque MT system” (in Spanish) and its English
Extended Abstract)
by A.Diaz de Ilarraza, A. Mayor and K. Sarasola presents a Rule-Based MT System
(English-Basque). This system has the particularity to be assembled out of
different resources and machineries, which may be one approach to be followed
when different MT-engines have to be combined into one system. For reasons such
as the treatment of translation ambiguities, the authors intend to continue
this assemblage by integrating methods based on statistics or examples.
Translation Memories
In his contribution Towards a Closer Integration of Termbases,
Translation Memories, and Parallel Corpora - A Translation - Oriented View,
Reinke takes a view from the translators point of view and complains about the
current state of the art in TM technology. He argues for a stronger integration
of termtools into TM. Termtools should be extended with 'implicit' translation
knowledge contained in the texts. This knowledge should then be used in the
alignment step to find subsentential translation units, which can increase
performance of these TMs. He criticizes the skeleton approach by Langi} et. al.
as being too shallow, and proposes a proper approach. However, current TM
technologies not only don't use 'explicit' knowledge in termbases but also have
no means to discover implicit terminological information or perform
subsentential alignment.
In "Evaluierung der linguistischen Leistungsfähigkeit von
Translation Memory-Systemen - Ein Erfahrungsbericht " (English
Abstract), Reinke tackles the difficult question of similarity in TMs.
Starting from the GLDV - workshop statement that evaluation criteria should be
different for MT and TM technology, he argues that TMs have more in common with
IR systems than with MT technology. Accordingly, TM evaluation can be handled
with retrieval performance in terms of precision and recall. He shows that the
TM-evaluation proposals in the EAGLES report are too vague and proposes to
consider semantic, pragmatic and conceptual similarities in place of
orthographic similarities only, as used in up-to-date TMs. In an original
experiment he feeds TMs with lemmatized forms in order to come closer a well
founded similarity notion.
Comparing and Linking different Architectures
Carl and Hansen pick up that idea in “Linking Translation Memories with
Example-Based Machine Translation”
and compare the translation outcome of a lemmatized TM and a string-based TM
(STM) with the translation outcome of an Example-Based Machine Translation
(EBMT) system. Their intention is to find a setting where a linkage of the
different translation paradigms is most reasonable. For each system, strengths
and shortcomings are discussed and it is shown in what way translation
ambiguities are produced. Based on a fully automatic evaluation method, they
show that a combination of a TM and EBMT is more successful than any single
system and that the linkage of STM and EBMT performs best.
In “Towards a Model of Competence for
Corpus-Based Machine Translation”
Michael Carl defines translation as a multi-layered mapping of the source text
description into an equivalent target text description. As different levels of
description may require a controversial realization in the target language an
ideal translations may not always be found. Accordingly he claims that
unrestricted all-purpose MT system is unfeasibel. A number of corpus-based MT
systems is examined according to the granularity, molecularity and
representational richness they have. The expected translation performance is
classified in terms of coverage and reliability. It is concluded that coarser
representations are likely to achieve higher reliability while richer
representations are due for broad coverage.
The contribution “Towards a Dynamic Linkage of Example-Based
and Rule-Base Machine Translation”
reports a number of translation experiments that link TM and EBMT with RBMT.
The authors (Carl, Iomdin, Pease and Streiter) start by examining the
potentials of each MT paradigm in terms of translation quality and coverage,
adaptability of the system and recall of TUs. The paper argues for a dynamic
linkage of different MT paradigms where the decision is taken at runtime in
what way to share the translation task amongst the systems. The paper motivates
the communication of rich data-structures between system components and show
that such a linkage leads to better translation results and improves
customization of the system.
In the paper “A Unified Example-Based and Lexicalist Approach to Machine
Translation”,
Turcato, McFetridge, Popowich and Toole propose a knowledge representation
format and a system architecture that allow an effective integration of
Example-Based and Lexicalist approaches to MT into a unified approach, which
the authors call Example-Based Lexicalist Machine Translation (EBLMT). This
approach tries to combine the advantages of each approach. From the point of
view of LMT, it uses bilingual knowledge to drive parsing, providing additional
information to solve syntactic ambiguities and prioritizing the parsing agenda
in a more efficient way. From the point of view of an EBMT system like [Sato
& Nagao1990], for instance, it allows the removal of the bilingual
database's redundancy coming from the overlap of examples.
Statistics and Learning
“Learning, Forgetting and Remembering: Statistical Support for
Rule-Based MT”
and Learning from
Parallel Corpora: Experiments in Machine Translation
represent two consecutive studies in which the authors (Streiter, Iomdin, Hong
and Hauck, resp. Iomdin and Streiter) investigate in how fare Rule-Based
Machine Translation Systems can benefit from monolingual and bilingual corpora.
Although monolingual corpora have obvious limitations, they can support the
translation process if the corpora and the translation task can be classified
as belonging to a subject domain. Bilingual corpora not only allow a better
evaluation of translation probabilities, but also the acquisition of new one-
and many-word translations. Two alignment techniques are proposed which do not
require a sentence alignment before sub-sentential chunks are aligned.
Automatic
Acquisition of a High-Precision Translation Lexicon from Parallel
Chinese-English Corpora (written by Zhao-Ming Gao) contains a hybrid approach
to deriving a translation lexicon from unaligned parallel Chinese-English
corpora. Two types of information, namely, proximity and document-external
distributions of word pairs, are proposed to enhance the precision of the
translation lexicon derived from statistical and dictionary-based methods. The
former can identify translations of Chinese compounds, while the latter can
filter out spurious word correspondences.
Special linguistic phenomena of spoken
language, the so-called closed captions, are the subject of the last paper. In “Explanation-based Learning for Machine
Translation”,
Toole, Popowich, Nicholson, Turcato and McFetridge present an application of
explanation-based learning (EBL) in the parsing module of a real-time
English-Spanish machine translation system designed to translate closed
captions. They discuss the efficiency/coverage trade-offs available in EBL and
introduce techniques to increase coverage while maintaining a high level of
space and time efficiency.
We hope to have assembled a first
representative set of approaches to the research paradigm of hybrid Machine
Translation which is an interesting field both from theoretical and from
practical point of view.
April, 2000
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Oliver
Streiter
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Michael Carl
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Johann Haller
|
|
Academia Sinica
Institute of Information Science
Nankang, Taipei, Taiwan 115
|
IAI
Institute of Applied Information Sciences
66111 Saarbrücken, Germany
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oliver@iis.sinica.edu.tw
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carl@iai.uni-sb.de
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hans@iai.uni-sb.de
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Linguistic
and computational Motivations for the LOGOS Machine Translation System
Bernard E. Scott (in English)
Reusability of wide coverage linguistic
resources in the construction of an English-Basque MT system
Ilarraza, Mayor and Sarasola [see MT2000, Exter
University]
Towards a
Closer Integration of Termbases, Translation Memories, and Parallel Corpora - A
Translation - Oriented View -
Uwe Reinke (in English)
Evaluierung der linguistischen
Leistungsfähigkeit von Translation Memory-Systemen - Ein Erfahrungsbericht
Uwe Reinke (in German, English Abstract)
Linking Translation Memories
with Example-Based Machine Translation
Michael Carl and Silvia Hansen (in English) [see MT
Summit VII]
Towards a Model of Competence for
Corpus-Based Machine Translation
Carl (in English) [see Coling 2000]
Towards a Dynamic Linkage of Example-Based
and Rule-Base Machine Translation
Michael Carl, Leonid L. Iomdin, Cathrine Pease and Oliver Streiter (in English)
[see ESSLLI 1998]
A Unified Example-Based and Lexicalist
Approach to Machine Translation
Davide Turcato, Paul McFetridge, Fred Popowich and Janine Toole (in English) [see
TMI-99]
Learning, Forgetting and Remembering:
Statistical Support for Rule-Based MT
Oliver Streiter, Leonid L. Iomdin, Munpyo Hong and Ute Hauck (in English) [see TMI-99]
Learning from
Parallel Corpora: Experiments in Machine Translation
Leonid L. Iomdin and Oliver Streiter (in English, abstract in Russian)
Explanation-based Learning for Machine
Translation
Janine Toole, Fred Popowich, Devlan Nicholson, Davide Turcato and Paul
McFetridge (in English) [see TMI-99]
Automatic
Acquisition of a High-Precision Translation Lexicon from Parallel
Chinese-English Corpora
Zhao-Ming Gao (in English)
Bibliography
The copyright of the contributions remains
with the authors.