2006

Linguistic Aspects in

Machine Translation

This paper will give a general overview of the venture that is machine

translation with particular focus on linguistic aspects. It will display history of

MT and will deal with some of the major issues in the realisation of MT like the

difficulty of translating prepositions or integrating semantics, as well as the

importance of real world knowledge. To illustrate these difficulties with

examples on a basic level, a practice test with a moderately complex translation

engine provided by Google has been carried out and will be explained. Final y, I

am going to introduce three of the largest and most powerful translation

machines currently in use. I will also give a brief over-view of methods of MT.

The aim of this paper is to show that the realisation of the primal idea of

machine translation in its original sense, which was to perform translation

without human intervention (except during the construction phase of the

system), is still markedly far away at present and machines are still unlikely to

take over the jobs of human translators.

Alexander Täuschel

18.01.2006

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Table of Contents

I.

Introduction 1

I. 1.)

What is Machine Translation? 1

I. 2.)

Why Machine Translation Matters 1

I. 2. a)

Social and Political Importance of MT 1

I. 2. b)

Scientific Importance of MT 2

I. 2. c)

Commercial Importance of MT 2

I. 2. d)

Philosophical Importance of MT 2

II.

The History of Machine Translation 3

II. 1.) The First Years of Translation Machines 3

II. 2.) A Pioneer: Warren Weaver, Founder of the Idea of MT 4

II. 3.) The Latter Years in MT 6

III.

Machine Translation in Practice 6

III. 1.) MT Test: Google 7

III. 2.) To Avoid Mistakes 9

IV.

Linguistic Aspects in MT 10

IV. 1.) Semantics 10

IV. 2.) Pragmatics 12

IV. 3.) Real World Knowledge 12

V.

Computational Linguistics 13

V. 1.) Methods of MT 13

V. 2.) Commonly Acknowledged Translation Systems 14

V. 2. a) LOGOS 15

V. 2. b) METAL 16

V. 2. c) METEO 16

VI.

Epilogue: On the Future of MT 17

VII.

Bibliography 19

VII. 1.) Literature 19

VII. 2.) Internet Sources 20

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LINGUISTIC ASPECTS IN MACHINE TRANSLATION

ALEXANDER TAEUSCHEL

I. Introduction

I. 1.)

What is Machine Translation?

A translation machine is a specialised software system developed for the translating from one

human language to another: "[Machine translation systems are actually not

machines

, rather to be

thought of] as programs that run on computers, which real y are machines" (Arnold et al.

1994:10). Machine translation, or as it was cal ed in its early days: Mechanical Translation (hence-

forth abbreviated as MT) is a subfield of artificial intelligence (AI), both belonging to the large area

of computer science (CS).

The field of machine translation is widely considered as one of the most awkward issues in

computational linguistics, because it requires interdisciplinary knowledge of the scientists involved

in the development of translation machines: knowledge in informatics, language cognition, skil s in

translating and in language description methods, as well as specialised knowledge in the fields the

texts, which are to be translated, deal with (see: Schwanke 1991:11).

Furthermore, if translation machines were able to take over translational work completely,

they would have to cover al capacities of a human translator: Human translators have to set a

pragmatical or aesthetical balance between the source text and the target text (see: Wilss

1988:VII). Applying skills, as well as language and transcultural knowledge are some of the transla-

tor′s optional tools to reach the expectations of the source text writer and the target text reader.

Another tool, according to Wilss, was a translator′s "intuition". He suggests that it was "some kind

of sixth sense", "the opposite of calculatable dynamics", a part of the translator′s mysterious, no-

torious "black box", whose existence was not unknown, but which we only had an

intuitive

image

of. Wilss adds that intuition was a "mental axiom" that could not be chal enged (129).

So if a translator′s `intuition′ is so hard to define, how can it be synthesised within computer

software, within a machine?

For a start, these reasons can only give a clue of what is at least involved in the development

of translation machines. Thus, the enthusiasm and belief in the future of computers taking over

and handling the translation of human languages has see-sawed since the birthing of its idea.

I. 2.)

Why Machine Translation Matters

MT was "one of the earliest applications" (Arnold et al. 1994:iii) suggested for digital1 com-

puters2 and like an artist might argue that a painting is never real y finished, the whole develop-

ment of computer science is still in process ­ and so is the "long-term scientific dream" of MT.

Also, the issue of MT contains increasing importance in several different fields of human en-

terprise; which wil be explained in the fol owing:

I. 2. a)

Social and Political Importance of MT

Its social and political importance "arises from the socio-political importance of translation in

communities where more than one language is generally spoken" (4), and where the adoption of a

common lingua franca is proximate. This ­ on the other hand ­ involves the dominance of the cho-

sen language among the community to the disadvantage of the speakers of the other language(s).

1

digit

(lat.): finger (Savetz)

2

computare

(lat.): to reckon (Savetz)

1

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LINGUISTIC ASPECTS IN MACHINE TRANSLATION

ALEXANDER TAEUSCHEL

This other language(s) can then become "second class" or disappear in the worst case, which is

undoubtedly something that should matter, because it involves potential loss of culture as well as

ways and uses of thinking and living. "So translation is necessary for communication (...)", even if it

means putting up with the side effects of it, like modifying or by chance, even losing semantic

or/and cultural details of the information which is to be translated into a different language, and

to be made accessible for another cultural community respectively. But since the modern world′s

demand for translation "far outstrips any possible supply", that is because of the actual deficiency

of human translators and capacity; "the automation of translation is a social and political necessity

for modern societies which do not wish to impose a common language on their members". Cases

like the Spanish speaking parts of the USA or the Welsh speaking parts of Great Britain make this

point obvious. Switzerland or the European Community, in which multilingualism is part of every-

day life, even more do so.

I. 2. b)

Scientific Importance of MT

The scientific importance of MT results from its quality of being an interesting application and

testing ground for ideas in CS, AI, and Linguistics ­ from which some of the most important devel-

opments have begun in MT, like: the origins of Prolog,3 the first widely available logic program-

ming language, which formed a key part of the Japanese Fifth Generation programme,4 were

originally developed for MT (see: 5).

I. 2. c)

Commercial Importance of MT

In today′s world of business the commercial importance of MT is not to be underestimated.

Firstly: As a matter of accessibility, a customer is more probable to buy a Japanese product with a

manual written in English than one whose manual is written in Japanese; even more so, when hav-

ing to buy a safety critical system. Secondly: translation is expensive and requires highly skilled

(and paid) workers. An average human translator may be able to manage 4-6 pages a day (see:

1994:5), which may cause delays during the development and the launching of a new product. Up

to 40-45% of the running costs of European Community institutions are `language costs′, "of which

translating and interpreting are the main element" (1994:5). The costs per year would make out

about £300 mil ion ­ a figure only relating to translations actually being done, not the amount of

translation being required (see: Patterson 1982).

I. 2. d)

Philosophical Importance of MT

MT is also a philosophical chal enge, because "it represents the attempt to automate an activ-

ity that can require the ful range of human knowledge (...): "The extend to which one can auto-

mate translation is an indication of the extend to which one can automate `thinking′" (Arnold et al.

1994:5).

3

Prolog

= short for PROgramming in LOGic was created by Alain Colmerauer (1941-) et al. in Marseille dur-

ing the 1970s. At the University of Edinburgh the work was finished with the support of Clocksin and Mellish.

And today their version called Edinburgh syntax is commonly acknowledged as standard (see:

<www.pcai.com>.)

4

Fifth Generation

= a "Japanese billion-dollar project, with a target date of 1989 to design and build a com-

puter that is not only a hundred times faster than a Cray `supercomputer′ (the so-called Cray-1 system which

was built by Cray Inc. in 1976 with a speed of 160 megaflops and an 8 MB memory; for further information

see: www.cray.com) but contains AI software as well" (Savetz); also see chapter III. 3.) of this paper.

2

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LINGUISTIC ASPECTS IN MACHINE TRANSLATION

ALEXANDER TAEUSCHEL

II. The History of Machine Translation

II. 1.) The First Years of Translation Machines

Ideas about mechanising translation processes can be traced back to the seventeenth century,

in connection with ideas on `real characters′ and `universal′ or `philosophical languages′, but it was

not until the 20th century, until it came to realistic possibilities: In the mid 1930s, a French-

Armenian, named Georges Artsrouni and a Russian, named Petr Smirnov-Trojanskij, who remained

unrecognized in the USSR (see: Schwanke 1991:69), both applied for patents for `translating ma-

chines′. Their idea contained not only a method for an automatic bilingual dictionary, but also a

scheme for coding interlingual grammatical roles, based on Esperanto, and ideas for analysing sen-

tences and generating texts in other languages. Neither one of them nor their ideas were known

to anyone involved in the latter putting forward of the first tentative ideas for using the new in-

vention ­ computers ­ for translating natural languages.

Pioneers in MT came from a wide variety of backgrounds, like electrical engineering, physics,

linguistics, interpretation or philosophy. Two of these pioneers were Andrew Booth and Warren

Weaver (1894-1978), who are particularly referred to in chapter II. 2.) of this paper.

In the earliest period, the question of what constituted an intermediary language (`interlin-

gua′;5 which is how the actual part of work done by the translation machine is named, because the

whole act required ­ and still requires ­ pre-editing and post-editing by a human; see: Schwanke

1991:69) and how it might be created preoccupied many researchers. It was closely related to in

the minds of many at the time with what was seen as paral el activity in the field of information

retrieval6 towards a universally applicable `information language′. The public interest and the at-

tention of those different scientific disciplines drawn to this new task was widespread to such ex-

tend, that it was not surprising that presentations of MT took place at a wide range of confer-

ences, wherever there was interest in the use of computers for exploring language and communi-

cation; for instance conferences on cybernetics, information retrieval, linguistics etc. The publicity

which statements about the immediate prospects of working systems attracted was not always

welcome by those in the field, because it raised the public hopes higher and higher.

With time, the attention was drawn to the limitations of dictionary-based systems and to the

importance of analysing and transforming syntactic structures; and from the 1960s onwards the

common focus of nearly all the MT groups was on syntax. There was initial interest in the theories

of Chomsky, but in time computers for syntactic structure analysis developed independently of the

dominant developments in theoretical linguistics. The basic system design moved away from the

earlier `direct translation′ approach7, and overall design was tending towards a three (or more)

stage approach involving independent processes of analysis, transfer, and synthesis.

Pioneers in MT had to face manifold and complex problems:

· Computers were for a long time limited in storage and speed, expensive to use and not

widely available (in the case of the USSR unavailable until the 1970s, and even then they

were far behind American models in capacity and speed).

· Input was cumbersome: texts had to be laboriously coded onto punched cards, because

most groups devised their own coding systems.

5 also see V. 1.) of this paper

6

information retrieval

= the use of computers to indentify and access documents relevant to particular query

(see: Hutchins 2000:2)

7

direct translation

= essentially built on word-for-word lexical substitution and structure modification (see: 3)

3

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