<s>
Machine	B-Application
translation	I-Application
,	O
sometimes	O
referred	O
to	O
by	O
the	O
abbreviation	O
MT	O
(	O
not	O
to	O
be	O
confused	O
with	O
computer-aided	B-Application
translation	I-Application
,	O
machine-aided	B-Application
human	I-Application
translation	I-Application
or	O
interactive	B-General_Concept
translation	I-General_Concept
)	O
,	O
is	O
a	O
sub-field	O
of	O
computational	O
linguistics	O
that	O
investigates	O
the	O
use	O
of	O
software	O
to	O
translate	O
text	O
or	O
speech	O
from	O
one	O
language	O
to	O
another	O
.	O
</s>
<s>
Current	O
machine	B-Application
translation	I-Application
software	O
often	O
allows	O
for	O
customization	O
by	O
domain	O
or	O
profession	O
(	O
such	O
as	O
weather	O
reports	O
)	O
,	O
improving	O
output	O
by	O
limiting	O
the	O
scope	O
of	O
allowable	O
substitutions	O
.	O
</s>
<s>
It	O
follows	O
that	O
machine	B-Application
translation	I-Application
of	O
government	O
and	O
legal	O
documents	O
more	O
readily	O
produces	O
usable	O
output	O
than	O
machine	B-Application
translation	I-Application
of	O
conversation	O
or	O
less	O
standardised	O
text	O
.	O
</s>
<s>
Improved	O
output	O
quality	O
can	O
also	O
be	O
achieved	O
by	O
human	O
intervention	O
:	O
for	O
example	O
,	O
some	O
systems	O
are	O
able	O
to	O
translate	O
more	O
accurately	O
if	O
the	O
user	O
has	O
unambiguously	B-General_Concept
identified	I-General_Concept
which	O
words	O
in	O
the	O
text	O
are	O
proper	O
names	O
.	O
</s>
<s>
The	O
progress	O
and	O
potential	O
of	O
machine	B-Application
translation	I-Application
have	O
been	O
much	O
debated	O
through	O
its	O
history	O
.	O
</s>
<s>
Since	O
the	O
1950s	O
,	O
a	O
number	O
of	O
scholars	O
,	O
first	O
and	O
most	O
notably	O
Yehoshua	O
Bar-Hillel	O
,	O
have	O
questioned	O
the	O
possibility	O
of	O
achieving	O
fully	O
automatic	O
machine	B-Application
translation	I-Application
of	O
high	O
quality	O
.	O
</s>
<s>
The	O
origins	O
of	O
machine	B-Application
translation	I-Application
can	O
be	O
traced	O
back	O
to	O
the	O
work	O
of	O
Al-Kindi	O
,	O
a	O
ninth-century	O
Arabic	B-General_Concept
cryptographer	O
who	O
developed	O
techniques	O
for	O
systemic	O
language	O
translation	O
,	O
including	O
cryptanalysis	O
,	O
frequency	O
analysis	O
,	O
and	O
probability	O
and	O
statistics	O
,	O
which	O
are	O
used	O
in	O
modern	O
machine	B-Application
translation	I-Application
.	O
</s>
<s>
The	O
idea	O
of	O
machine	B-Application
translation	I-Application
later	O
appeared	O
in	O
the	O
17th	O
century	O
.	O
</s>
<s>
A	O
demonstration	O
was	O
made	O
in	O
1954	O
on	O
the	O
APEXC	B-Device
machine	O
at	O
Birkbeck	O
College	O
(	O
University	O
of	O
London	O
)	O
of	O
a	O
rudimentary	O
translation	O
of	O
English	O
into	O
French	O
.	O
</s>
<s>
A	O
Georgetown	O
University	O
MT	O
research	O
team	O
,	O
led	O
by	O
Professor	O
Michael	O
Zarechnak	O
,	O
followed	O
(	O
1951	O
)	O
with	O
a	O
public	O
demonstration	O
of	O
its	O
Georgetown-IBM	B-General_Concept
experiment	I-General_Concept
system	O
in	O
1954	O
.	O
</s>
<s>
Researchers	O
continued	O
to	O
join	O
the	O
field	O
as	O
the	O
Association	O
for	O
Machine	B-Application
Translation	I-Application
and	O
Computational	O
Linguistics	O
was	O
formed	O
in	O
the	O
U.S.	O
(	O
1962	O
)	O
and	O
the	O
National	O
Academy	O
of	O
Sciences	O
formed	O
the	O
Automatic	B-General_Concept
Language	I-General_Concept
Processing	I-General_Concept
Advisory	I-General_Concept
Committee	I-General_Concept
(	O
ALPAC	B-General_Concept
)	O
to	O
study	O
MT	O
(	O
1964	O
)	O
.	O
</s>
<s>
Real	O
progress	O
was	O
much	O
slower	O
,	O
however	O
,	O
and	O
after	O
the	O
ALPAC	B-General_Concept
report	I-General_Concept
(	O
1966	O
)	O
,	O
which	O
found	O
that	O
the	O
ten-year-long	O
research	O
had	O
failed	O
to	O
fulfill	O
expectations	O
,	O
funding	O
was	O
greatly	O
reduced	O
.	O
</s>
<s>
The	O
French	O
Textile	O
Institute	O
also	O
used	O
MT	O
to	O
translate	O
abstracts	O
from	O
and	O
into	O
French	O
,	O
English	O
,	O
German	O
and	O
Spanish	O
(	O
1970	O
)	O
;	O
Brigham	O
Young	O
University	O
started	O
a	O
project	O
to	O
translate	O
Mormon	O
texts	O
by	O
automated	B-Application
translation	I-Application
(	O
1971	O
)	O
.	O
</s>
<s>
SYSTRAN	B-General_Concept
,	O
which	O
"	O
pioneered	O
the	O
field	O
under	O
contracts	O
from	O
the	O
U.S.	O
government	O
"	O
in	O
the	O
1960s	O
,	O
was	O
used	O
by	O
Xerox	O
to	O
translate	O
technical	O
manuals	O
(	O
1978	O
)	O
.	O
</s>
<s>
Beginning	O
in	O
the	O
late	O
1980s	O
,	O
as	O
computational	O
power	O
increased	O
and	O
became	O
less	O
expensive	O
,	O
more	O
interest	O
was	O
shown	O
in	O
statistical	B-General_Concept
models	I-General_Concept
for	I-General_Concept
machine	I-General_Concept
translation	I-General_Concept
.	O
</s>
<s>
SYSTRAN	B-General_Concept
's	O
first	O
implementation	O
system	O
was	O
implemented	O
in	O
1988	O
by	O
the	O
online	O
service	O
of	O
the	O
French	O
Postal	O
Service	O
called	O
Minitel	O
.	O
</s>
<s>
Various	O
computer	O
based	O
translation	O
companies	O
were	O
also	O
launched	O
,	O
including	O
Trados	O
(	O
1984	O
)	O
,	O
which	O
was	O
the	O
first	O
to	O
develop	O
and	O
market	O
Translation	B-General_Concept
Memory	I-General_Concept
technology	O
(	O
1989	O
)	O
,	O
though	O
this	O
is	O
not	O
the	O
same	O
as	O
MT	O
.	O
</s>
<s>
MT	O
on	O
the	O
web	O
started	O
with	O
SYSTRAN	B-General_Concept
offering	O
free	O
translation	O
of	O
small	O
texts	O
(	O
1996	O
)	O
and	O
then	O
providing	O
this	O
via	O
AltaVista	O
Babelfish	O
,	O
which	O
racked	O
up	O
500,000	O
requests	O
a	O
day	O
(	O
1997	O
)	O
.	O
</s>
<s>
In	O
2012	O
,	O
Google	O
announced	O
that	O
Google	B-Application
Translate	I-Application
translates	O
roughly	O
enough	O
text	O
to	O
fill	O
1	O
million	O
books	O
in	O
one	O
day	O
.	O
</s>
<s>
Re-encoding	O
this	O
meaning	O
in	O
the	O
target	O
language	O
.	O
</s>
<s>
To	O
decode	O
the	O
meaning	O
of	O
the	O
source	O
text	O
in	O
its	O
entirety	O
,	O
the	O
translator	O
must	O
interpret	O
and	O
analyse	O
all	O
the	O
features	O
of	O
the	O
text	O
,	O
a	O
process	O
that	O
requires	O
in-depth	O
knowledge	O
of	O
the	O
grammar	O
,	O
semantics	B-Application
,	O
syntax	B-Application
,	O
idioms	O
,	O
etc.	O
,	O
of	O
the	O
source	O
language	O
,	O
as	O
well	O
as	O
the	O
culture	O
of	O
its	O
speakers	O
.	O
</s>
<s>
Therein	O
lies	O
the	O
challenge	O
in	O
machine	B-Application
translation	I-Application
:	O
how	O
to	O
program	O
a	O
computer	O
that	O
will	O
"	O
understand	O
"	O
a	O
text	O
as	O
a	O
person	O
does	O
,	O
and	O
that	O
will	O
"	O
create	O
"	O
a	O
new	O
text	O
in	O
the	O
target	O
language	O
that	O
sounds	O
as	O
if	O
it	O
has	O
been	O
written	O
by	O
a	O
person	O
.	O
</s>
<s>
Machine	B-Application
translation	I-Application
can	O
use	O
a	O
method	O
based	O
on	O
linguistic	B-Application
rules	I-Application
,	O
which	O
means	O
that	O
words	O
will	O
be	O
translated	O
in	O
a	O
linguistic	O
way	O
–	O
the	O
most	O
suitable	O
(	O
orally	O
speaking	O
)	O
words	O
of	O
the	O
target	O
language	O
will	O
replace	O
the	O
ones	O
in	O
the	O
source	O
language	O
.	O
</s>
<s>
It	O
is	O
often	O
argued	O
that	O
the	O
success	O
of	O
machine	B-Application
translation	I-Application
requires	O
the	O
problem	O
of	O
natural	B-General_Concept
language	I-General_Concept
understanding	I-General_Concept
to	O
be	O
solved	O
first	O
.	O
</s>
<s>
According	O
to	O
the	O
nature	O
of	O
the	O
intermediary	O
representation	O
,	O
an	O
approach	O
is	O
described	O
as	O
interlingual	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
or	O
transfer-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
.	O
</s>
<s>
These	O
methods	O
require	O
extensive	O
lexicons	B-Application
with	O
morphological	O
,	O
syntactic	B-Application
,	O
and	O
semantic	B-Application
information	O
,	O
and	O
large	O
sets	O
of	O
rules	O
.	O
</s>
<s>
Given	O
enough	O
data	O
,	O
machine	B-Application
translation	I-Application
programs	O
often	O
work	O
well	O
enough	O
for	O
a	O
native	O
speaker	O
of	O
one	O
language	O
to	O
get	O
the	O
approximate	O
meaning	O
of	O
what	O
is	O
written	O
by	O
the	O
other	O
native	O
speaker	O
.	O
</s>
<s>
To	O
translate	O
between	O
closely	O
related	O
languages	O
,	O
the	O
technique	O
referred	O
to	O
as	O
rule-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
may	O
be	O
used	O
.	O
</s>
<s>
The	O
rule-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
paradigm	O
includes	O
transfer-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
,	O
interlingual	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
and	O
dictionary-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
paradigms	O
.	O
</s>
<s>
This	O
type	O
of	O
translation	O
is	O
used	O
mostly	O
in	O
the	O
creation	O
of	O
dictionaries	B-Operating_System
and	O
grammar	O
programs	O
.	O
</s>
<s>
Unlike	O
other	O
methods	O
,	O
RBMT	B-General_Concept
involves	O
more	O
information	O
about	O
the	O
linguistics	O
of	O
the	O
source	O
and	O
target	O
languages	O
,	O
using	O
the	O
morphological	O
and	O
syntactic	B-Application
rules	O
and	O
semantic	B-Application
analysis	O
of	O
both	O
languages	O
.	O
</s>
<s>
The	O
basic	O
approach	O
involves	O
linking	O
the	O
structure	O
of	O
the	O
input	O
sentence	O
with	O
the	O
structure	O
of	O
the	O
output	O
sentence	O
using	O
a	O
parser	O
and	O
an	O
analyzer	O
for	O
the	O
source	O
language	O
,	O
a	O
generator	O
for	O
the	O
target	O
language	O
,	O
and	O
a	O
transfer	O
lexicon	B-Application
for	O
the	O
actual	O
translation	O
.	O
</s>
<s>
RBMT	B-General_Concept
's	O
biggest	O
downfall	O
is	O
that	O
everything	O
must	O
be	O
made	O
explicit	O
:	O
orthographical	O
variation	O
and	O
erroneous	O
input	O
must	O
be	O
made	O
part	O
of	O
the	O
source	O
language	O
analyser	O
in	O
order	O
to	O
cope	O
with	O
it	O
,	O
and	O
lexical	O
selection	O
rules	O
must	O
be	O
written	O
for	O
all	O
instances	O
of	O
ambiguity	O
.	O
</s>
<s>
Transfer-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
is	O
similar	O
to	O
interlingual	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
in	O
that	O
it	O
creates	O
a	O
translation	O
from	O
an	O
intermediate	O
representation	O
that	O
simulates	O
the	O
meaning	O
of	O
the	O
original	O
sentence	O
.	O
</s>
<s>
Interlingual	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
is	O
one	O
instance	O
of	O
rule-based	O
machine-translation	O
approaches	O
.	O
</s>
<s>
However	O
,	O
the	O
only	O
interlingual	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
system	O
that	O
has	O
been	O
made	O
operational	O
at	O
the	O
commercial	O
level	O
is	O
the	O
KANT	O
system	O
(	O
Nyberg	O
and	O
Mitamura	O
,	O
1992	O
)	O
,	O
which	O
is	O
designed	O
to	O
translate	O
Caterpillar	O
Technical	O
English	O
(	O
CTE	O
)	O
into	O
other	O
languages	O
.	O
</s>
<s>
Machine	B-Application
translation	I-Application
can	O
use	O
a	O
method	O
based	O
on	O
dictionary	B-Operating_System
entries	O
,	O
which	O
means	O
that	O
the	O
words	O
will	O
be	O
translated	O
as	O
they	O
are	O
by	O
a	O
dictionary	B-Operating_System
.	O
</s>
<s>
Statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
tries	O
to	O
generate	O
translations	O
using	O
statistical	O
methods	O
based	O
on	O
bilingual	O
text	O
corpora	O
,	O
such	O
as	O
the	O
Canadian	O
Hansard	O
corpus	O
,	O
the	O
English-French	O
record	O
of	O
the	O
Canadian	O
parliament	O
and	O
EUROPARL	O
,	O
the	O
record	O
of	O
the	O
European	O
Parliament	O
.	O
</s>
<s>
The	O
first	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
software	O
was	O
CANDIDE	O
from	O
IBM	O
.	O
</s>
<s>
Google	O
used	O
SYSTRAN	B-General_Concept
for	O
several	O
years	O
,	O
but	O
switched	O
to	O
a	O
statistical	B-General_Concept
translation	I-General_Concept
method	O
in	O
October	O
2007	O
.	O
</s>
<s>
Google	B-Application
Translate	I-Application
and	O
similar	O
statistical	B-General_Concept
translation	I-General_Concept
programs	O
work	O
by	O
detecting	O
patterns	O
in	O
hundreds	O
of	O
millions	O
of	O
documents	O
that	O
have	O
previously	O
been	O
translated	O
by	O
humans	O
and	O
making	O
intelligent	O
guesses	O
based	O
on	O
the	O
findings	O
.	O
</s>
<s>
Newer	O
approaches	O
into	O
Statistical	B-General_Concept
Machine	I-General_Concept
translation	I-General_Concept
such	O
as	O
METIS	O
II	O
and	O
PRESEMT	O
use	O
minimal	O
corpus	O
size	O
and	O
instead	O
focus	O
on	O
derivation	O
of	O
syntactic	B-Application
structure	O
through	O
pattern	O
recognition	O
.	O
</s>
<s>
With	O
further	O
development	O
,	O
this	O
may	O
allow	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
to	O
operate	O
off	O
of	O
a	O
monolingual	O
text	O
corpus	O
.	O
</s>
<s>
Example-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
(	O
EBMT	B-General_Concept
)	O
approach	O
was	O
proposed	O
by	O
Makoto	O
Nagao	O
in	O
1984	O
.	O
</s>
<s>
Example-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
is	O
based	O
on	O
the	O
idea	O
of	O
analogy	O
.	O
</s>
<s>
Hybrid	O
machine	B-Application
translation	I-Application
(	O
HMT	O
)	O
leverages	O
the	O
strengths	O
of	O
statistical	O
and	O
rule-based	O
translation	O
methodologies	O
.	O
</s>
<s>
More	O
recently	O
,	O
with	O
the	O
advent	O
of	O
Neural	O
MT	O
,	O
a	O
new	O
version	O
of	O
hybrid	O
machine	B-Application
translation	I-Application
is	O
emerging	O
that	O
combines	O
the	O
benefits	O
of	O
rules	O
,	O
statistical	O
and	O
neural	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
.	O
</s>
<s>
A	O
deep	O
learning-based	O
approach	O
to	O
MT	O
,	O
neural	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
has	O
made	O
rapid	O
progress	O
in	O
recent	O
years	O
,	O
and	O
Google	O
has	O
announced	O
its	O
translation	O
services	O
are	O
now	O
using	O
this	O
technology	O
in	O
preference	O
over	O
its	O
previous	O
statistical	O
methods	O
.	O
</s>
<s>
Second	O
Conference	O
On	O
Machine	B-Application
Translation	I-Application
"	O
)	O
in	O
2018	O
,	O
marking	O
a	O
historical	O
milestone	O
.	O
</s>
<s>
To	O
address	O
the	O
idiomatic	O
phrase	O
translation	O
,	O
multi-word	O
expressions	O
,	O
and	O
low-frequency	O
words	O
(	O
also	O
called	O
OOV	O
,	O
or	O
out-of-vocabulary	O
word	O
translation	O
)	O
,	O
language-focused	O
linguistic	O
features	O
have	O
been	O
explored	O
in	O
state-of-the-art	O
neural	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
(	O
NMT	O
)	O
models	O
.	O
</s>
<s>
Translations	O
by	O
neural	O
MT	O
tools	O
like	O
DeepL	B-Language
Translator	I-Language
,	O
which	O
is	O
thought	O
to	O
usually	O
deliver	O
the	O
best	O
machine	B-Application
translation	I-Application
results	O
as	O
of	O
2022	O
,	O
typically	O
still	O
need	O
post-editing	O
by	O
a	O
human	O
.	O
</s>
<s>
Techniques	O
in	O
use	O
and	O
under	O
development	O
that	O
can	O
improve	O
machine	B-Application
translations	I-Application
beyond	O
training	O
-	O
and	O
training-data	O
(	O
mainly	O
parallel	O
corpora	O
)	O
related	O
techniques	O
include	O
:	O
</s>
<s>
Natural	B-Language
language	I-Language
processing	I-Language
–	O
enabling	O
semantic	B-Application
understanding	O
of	O
the	O
source	O
text	O
(	O
e.g.	O
</s>
<s>
In	O
a	O
study	O
a	O
"	O
semantic	B-Application
unit	O
library	O
"	O
was	O
used	O
to	O
complete	O
"	O
the	O
translation	O
in	O
combination	O
with	O
the	O
target	O
language	O
sentences	O
"	O
.	O
</s>
<s>
Common	O
issues	O
include	O
the	O
translation	O
of	O
ambiguous	O
parts	O
whose	O
correct	O
translation	O
requires	O
common	O
sense-like	O
semantic	B-Application
language	O
processing	O
or	O
context	O
.	O
</s>
<s>
Word-sense	B-General_Concept
disambiguation	I-General_Concept
concerns	O
finding	O
a	O
suitable	O
translation	O
when	O
a	O
word	O
can	O
have	O
more	O
than	O
one	O
meaning	O
.	O
</s>
<s>
Claude	O
Piron	O
,	O
a	O
long-time	O
translator	O
for	O
the	O
United	O
Nations	O
and	O
the	O
World	O
Health	O
Organization	O
,	O
wrote	O
that	O
machine	B-Application
translation	I-Application
,	O
at	O
its	O
best	O
,	O
automates	O
the	O
easier	O
part	O
of	O
a	O
translator	O
's	O
job	O
;	O
the	O
harder	O
and	O
more	O
time-consuming	O
part	O
usually	O
involves	O
doing	O
extensive	O
research	O
to	O
resolve	O
ambiguities	O
in	O
the	O
source	O
text	O
,	O
which	O
the	O
grammatical	O
and	O
lexical	O
exigencies	O
of	O
the	O
target	O
language	O
require	O
to	O
be	O
resolved	O
:	O
</s>
<s>
The	O
ideal	O
deep	O
approach	O
would	O
require	O
the	O
translation	B-Application
software	I-Application
to	O
do	O
all	O
the	O
research	O
necessary	O
for	O
this	O
kind	O
of	O
disambiguation	B-General_Concept
on	O
its	O
own	O
;	O
but	O
this	O
would	O
require	O
a	O
higher	O
degree	O
of	O
AI	B-Application
than	O
has	O
yet	O
been	O
attained	O
.	O
</s>
<s>
Limitations	O
on	O
translation	O
from	O
casual	O
speech	O
present	O
issues	O
in	O
the	O
use	O
of	O
machine	B-Application
translation	I-Application
in	O
mobile	O
devices	O
.	O
</s>
<s>
In	O
information	B-General_Concept
extraction	I-General_Concept
,	O
named	O
entities	O
,	O
in	O
a	O
narrow	O
sense	O
,	O
refer	O
to	O
concrete	O
or	O
abstract	O
entities	O
in	O
the	O
real	O
world	O
such	O
as	O
people	O
,	O
organizations	O
,	O
companies	O
,	O
and	O
places	O
that	O
have	O
a	O
proper	O
name	O
:	O
George	O
Washington	O
,	O
Chicago	O
,	O
Microsoft	O
.	O
</s>
<s>
The	O
term	O
rigid	O
designator	O
is	O
what	O
defines	O
these	O
usages	O
for	O
analysis	O
in	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
.	O
</s>
<s>
Words	O
like	O
these	O
are	O
hard	O
for	O
machine	B-Application
translators	I-Application
,	O
even	O
those	O
with	O
a	O
transliteration	O
component	O
,	O
to	O
process	O
.	O
</s>
<s>
If	O
the	O
stored	O
information	O
is	O
of	O
linguistic	O
nature	O
,	O
one	O
can	O
speak	O
of	O
a	O
lexicon	B-Application
.	O
</s>
<s>
In	O
NLP	B-Language
,	O
ontologies	O
can	O
be	O
used	O
as	O
a	O
source	O
of	O
knowledge	O
for	O
machine	B-Application
translation	I-Application
systems	I-Application
.	O
</s>
<s>
In	O
the	O
following	O
classic	O
examples	O
,	O
as	O
humans	O
,	O
we	O
are	O
able	O
to	O
interpret	O
the	O
prepositional	O
phrase	O
according	O
to	O
the	O
context	O
because	O
we	O
use	O
our	O
world	O
knowledge	O
,	O
stored	O
in	O
our	O
lexicons	B-Application
:	O
</s>
<s>
A	O
machine	B-Application
translation	I-Application
system	I-Application
initially	O
would	O
not	O
be	O
able	O
to	O
differentiate	O
between	O
the	O
meanings	O
because	O
syntax	B-Application
does	O
not	O
change	O
.	O
</s>
<s>
Other	O
areas	O
of	O
usage	O
for	O
ontologies	O
within	O
NLP	B-Language
include	O
information	B-Library
retrieval	I-Library
,	O
information	B-General_Concept
extraction	I-General_Concept
and	O
text	B-Application
summarization	I-Application
.	O
</s>
<s>
The	O
ontology	O
generated	O
for	O
the	O
PANGLOSS	O
knowledge-based	O
machine	B-Application
translation	I-Application
system	I-Application
in	O
1993	O
may	O
serve	O
as	O
an	O
example	O
of	O
how	O
an	O
ontology	O
for	O
NLP	B-Language
purposes	O
can	O
be	O
compiled	O
:	O
</s>
<s>
A	O
large-scale	O
ontology	O
is	O
necessary	O
to	O
help	O
parsing	O
in	O
the	O
active	O
modules	O
of	O
the	O
machine	B-Application
translation	I-Application
system	I-Application
.	O
</s>
<s>
The	O
goal	O
was	O
to	O
merge	O
the	O
two	O
resources	O
LDOCE	O
online	O
and	O
WordNet	B-General_Concept
to	O
combine	O
the	O
benefits	O
of	O
both	O
:	O
concise	O
definitions	O
from	O
Longman	O
,	O
and	O
semantic	B-Application
relations	O
allowing	O
for	O
semi-automatic	O
taxonomization	O
to	O
the	O
ontology	O
from	O
WordNet	B-General_Concept
.	O
</s>
<s>
A	O
definition	O
match	O
algorithm	O
was	O
created	O
to	O
automatically	O
merge	O
the	O
correct	O
meanings	O
of	O
ambiguous	O
words	O
between	O
the	O
two	O
online	O
resources	O
,	O
based	O
on	O
the	O
words	O
that	O
the	O
definitions	O
of	O
those	O
meanings	O
have	O
in	O
common	O
in	O
LDOCE	O
and	O
WordNet	B-General_Concept
.	O
</s>
<s>
A	O
second	O
hierarchy	O
match	O
algorithm	O
was	O
therefore	O
created	O
which	O
uses	O
the	O
taxonomic	O
hierarchies	O
found	O
in	O
WordNet	B-General_Concept
(	O
deep	O
hierarchies	O
)	O
and	O
partially	O
in	O
LDOCE	O
(	O
flat	O
hierarchies	O
)	O
.	O
</s>
<s>
Both	O
algorithms	O
complemented	O
each	O
other	O
and	O
helped	O
constructing	O
a	O
large-scale	O
ontology	O
for	O
the	O
machine	B-Application
translation	I-Application
system	I-Application
.	O
</s>
<s>
The	B-General_Concept
WordNet	I-General_Concept
hierarchies	O
,	O
coupled	O
with	O
the	O
matching	O
definitions	O
of	O
LDOCE	O
,	O
were	O
subordinated	O
to	O
the	O
ontology	O
's	O
upper	O
region	O
.	O
</s>
<s>
While	O
no	O
system	O
provides	O
the	O
ideal	O
of	O
fully	O
automatic	O
high-quality	O
machine	B-Application
translation	I-Application
of	O
unrestricted	O
text	O
,	O
many	O
fully	O
automated	O
systems	O
produce	O
reasonable	O
output	O
.	O
</s>
<s>
The	O
quality	O
of	O
machine	B-Application
translation	I-Application
is	O
substantially	O
improved	O
if	O
the	O
domain	O
is	O
restricted	O
and	O
controlled	O
.	O
</s>
<s>
This	O
enables	O
using	O
machine	B-Application
translation	I-Application
as	O
a	O
tool	O
to	O
speed	O
up	O
and	O
simplify	O
translations	O
,	O
as	O
well	O
as	O
producing	O
flawed	O
but	O
useful	O
low-cost	O
or	O
ad-hoc	O
translations	O
.	O
</s>
<s>
Machine	B-Application
translation	I-Application
applications	O
have	O
also	O
been	O
released	O
for	O
most	O
mobile	O
devices	O
,	O
including	O
mobile	O
telephones	O
,	O
pocket	O
PCs	O
,	O
PDAs	O
,	O
etc	O
.	O
</s>
<s>
Due	O
to	O
their	O
portability	O
,	O
such	O
instruments	O
have	O
come	O
to	O
be	O
designated	O
as	O
mobile	B-General_Concept
translation	I-General_Concept
tools	O
enabling	O
mobile	O
business	O
networking	O
between	O
partners	O
speaking	O
different	O
languages	O
,	O
or	O
facilitating	O
both	O
foreign	O
language	O
learning	O
and	O
unaccompanied	O
traveling	O
to	O
foreign	O
countries	O
without	O
the	O
need	O
of	O
the	O
intermediation	O
of	O
a	O
human	O
translator	O
.	O
</s>
<s>
For	O
example	O
,	O
the	O
Google	B-Application
Translate	I-Application
app	O
allows	O
foreigners	O
to	O
quickly	O
translate	O
text	O
in	O
their	O
surrounding	O
via	O
augmented	B-General_Concept
reality	I-General_Concept
using	O
the	O
smartphone	O
camera	O
that	O
overlays	O
the	O
translated	O
text	O
onto	O
the	O
text	O
.	O
</s>
<s>
It	O
can	O
also	O
recognize	B-Application
speech	I-Application
and	O
then	O
translate	O
it	O
.	O
</s>
<s>
The	O
European	O
Commission	O
contributed	O
3.072	O
million	O
euros	O
(	O
via	O
its	O
ISA	O
programme	O
)	O
for	O
the	O
creation	O
of	O
MT	O
@EC	O
,	O
a	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
program	O
tailored	O
to	O
the	O
administrative	O
needs	O
of	O
the	O
EU	O
,	O
to	O
replace	O
a	O
previous	O
rule-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
system	O
.	O
</s>
<s>
Machine	B-Application
translation	I-Application
has	O
also	O
be	O
used	O
for	O
translating	O
Wikipedia	O
articles	O
and	O
could	O
play	O
a	O
larger	O
role	O
in	O
creating	O
,	O
updating	O
,	O
expanding	O
,	O
and	O
generally	O
improving	O
articles	O
in	O
the	O
future	O
,	O
especially	O
as	O
the	O
MT	O
capabilities	O
may	O
improve	O
.	O
</s>
<s>
In-Q-Tel	O
(	O
a	O
venture	O
capital	O
fund	O
,	O
largely	O
funded	O
by	O
the	O
US	O
Intelligence	O
Community	O
,	O
to	O
stimulate	O
new	O
technologies	O
through	O
private	O
sector	O
entrepreneurs	O
)	O
brought	O
up	O
companies	O
like	O
Language	B-General_Concept
Weaver	I-General_Concept
.	O
</s>
<s>
Currently	O
the	O
military	O
community	O
is	O
interested	O
in	O
translation	O
and	O
processing	O
of	O
languages	O
like	O
Arabic	B-General_Concept
,	O
Pashto	O
,	O
and	O
Dari	O
.	O
</s>
<s>
The	O
notable	O
rise	O
of	O
social	O
networking	O
on	O
the	O
web	O
in	O
recent	O
years	O
has	O
created	O
yet	O
another	O
niche	O
for	O
the	O
application	O
of	O
machine	B-Application
translation	I-Application
software	O
–	O
in	O
utilities	O
such	O
as	O
Facebook	O
,	O
or	O
instant	B-Application
messaging	I-Application
clients	O
such	O
as	O
Skype	O
,	O
GoogleTalk	O
,	O
MSN	O
Messenger	O
,	O
etc	O
.	O
</s>
<s>
Despite	O
being	O
labelled	O
as	O
an	O
unworthy	O
competitor	O
to	O
human	O
translation	O
in	O
1966	O
by	O
the	O
Automated	O
Language	O
Processing	O
Advisory	O
Committee	O
put	O
together	O
by	O
the	O
United	O
States	O
government	O
,	O
the	O
quality	O
of	O
machine	B-Application
translation	I-Application
has	O
now	O
been	O
improved	O
to	O
such	O
levels	O
that	O
its	O
application	O
in	O
online	O
collaboration	O
and	O
in	O
the	O
medical	O
field	O
are	O
being	O
investigated	O
.	O
</s>
<s>
There	O
are	O
many	O
factors	O
that	O
affect	O
how	O
machine	B-Application
translation	I-Application
systems	I-Application
are	O
evaluated	O
.	O
</s>
<s>
These	O
factors	O
include	O
the	O
intended	O
use	O
of	O
the	O
translation	O
,	O
the	O
nature	O
of	O
the	O
machine	B-Application
translation	I-Application
software	O
,	O
and	O
the	O
nature	O
of	O
the	O
translation	O
process	O
.	O
</s>
<s>
For	O
example	O
,	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
(	O
SMT	O
)	O
typically	O
outperforms	O
example-based	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
(	O
EBMT	B-General_Concept
)	O
,	O
but	O
researchers	O
found	O
that	O
when	O
evaluating	O
English	O
to	O
French	O
translation	O
,	O
EBMT	B-General_Concept
performs	O
better	O
.	O
</s>
<s>
In	O
certain	O
applications	O
,	O
however	O
,	O
e.g.	O
,	O
product	O
descriptions	O
written	O
in	O
a	O
controlled	B-General_Concept
language	I-General_Concept
,	O
a	O
dictionary-based	B-General_Concept
machine-translation	I-General_Concept
system	O
has	O
produced	O
satisfactory	O
translations	O
that	O
require	O
no	O
human	O
intervention	O
save	O
for	O
quality	O
inspection	O
.	O
</s>
<s>
There	O
are	O
various	O
means	O
for	O
evaluating	O
the	O
output	O
quality	O
of	O
machine	B-Application
translation	I-Application
systems	I-Application
.	O
</s>
<s>
Automated	O
means	O
of	O
evaluation	O
include	O
BLEU	O
,	O
NIST	O
,	O
METEOR	B-Language
,	O
and	O
LEPOR	O
.	O
</s>
<s>
Relying	O
exclusively	O
on	O
unedited	O
machine	B-Application
translation	I-Application
ignores	O
the	O
fact	O
that	O
communication	O
in	O
human	O
language	O
is	O
context-embedded	O
and	O
that	O
it	O
takes	O
a	O
person	O
to	O
comprehend	O
the	O
context	O
of	O
the	O
original	O
text	O
with	O
a	O
reasonable	O
degree	O
of	O
probability	O
.	O
</s>
<s>
The	O
late	O
Claude	O
Piron	O
wrote	O
that	O
machine	B-Application
translation	I-Application
,	O
at	O
its	O
best	O
,	O
automates	O
the	O
easier	O
part	O
of	O
a	O
translator	O
's	O
job	O
;	O
the	O
harder	O
and	O
more	O
time-consuming	O
part	O
usually	O
involves	O
doing	O
extensive	O
research	O
to	O
resolve	O
ambiguities	O
in	O
the	O
source	O
text	O
,	O
which	O
the	O
grammatical	O
and	O
lexical	O
exigencies	O
of	O
the	O
target	O
language	O
require	O
to	O
be	O
resolved	O
.	O
</s>
<s>
In	O
addition	O
to	O
disambiguation	B-General_Concept
problems	O
,	O
decreased	O
accuracy	O
can	O
occur	O
due	O
to	O
varying	O
levels	O
of	O
training	O
data	O
for	O
machine	O
translating	O
programs	O
.	O
</s>
<s>
Both	O
example-based	O
and	O
statistical	B-General_Concept
machine	I-General_Concept
translation	I-General_Concept
rely	O
on	O
a	O
vast	O
array	O
of	O
real	O
example	O
sentences	O
as	O
a	O
base	O
for	O
translation	O
,	O
and	O
when	O
too	O
many	O
or	O
too	O
few	O
sentences	O
are	O
analyzed	O
accuracy	O
is	O
jeopardized	O
.	O
</s>
<s>
Flaws	O
in	O
machine	B-Application
translation	I-Application
have	O
been	O
noted	O
for	O
their	O
entertainment	O
value	O
.	O
</s>
<s>
Two	O
videos	O
uploaded	O
to	O
YouTube	B-General_Concept
in	O
April	O
2017	O
involve	O
two	O
Japanese	O
hiragana	O
characters	O
えぐ	O
(	O
e	O
and	O
gu	O
)	O
being	O
repeatedly	O
pasted	O
into	O
Google	B-Application
Translate	I-Application
,	O
with	O
the	O
resulting	O
translations	O
quickly	O
degrading	O
into	O
nonsensical	O
phrases	O
such	O
as	O
"	O
DECEARING	O
EGG	O
"	O
and	O
"	O
Deep-sea	O
squeeze	O
trees	O
"	O
,	O
which	O
are	O
then	O
read	O
in	O
increasingly	O
absurd	O
voices	O
;	O
the	O
full-length	O
version	O
of	O
the	O
video	O
currently	O
has	O
6.9	O
million	O
views	O
as	O
of	O
March	O
2022	O
.	O
</s>
<s>
Although	O
there	O
have	O
been	O
concerns	O
about	O
machine	B-Application
translation	I-Application
's	O
accuracy	O
,	O
Dr.	O
Ana	O
Nino	O
of	O
the	O
University	O
of	O
Manchester	O
has	O
researched	O
some	O
of	O
the	O
advantages	O
in	O
utilizing	O
machine	B-Application
translation	I-Application
in	O
the	O
classroom	O
.	O
</s>
<s>
In	O
the	O
early	O
2000s	O
,	O
options	O
for	O
machine	B-Application
translation	I-Application
between	O
spoken	O
and	O
signed	O
languages	O
were	O
severely	O
limited	O
.	O
</s>
<s>
The	O
program	O
would	O
first	O
analyze	O
the	O
syntactic	B-Application
,	O
grammatical	O
,	O
and	O
morphological	O
aspects	O
of	O
the	O
English	O
text	O
.	O
</s>
<s>
Following	O
this	O
step	O
,	O
the	O
program	O
accessed	O
a	O
sign	O
synthesizer	O
,	O
which	O
acted	O
as	O
a	O
dictionary	B-Operating_System
for	O
ASL	O
.	O
</s>
<s>
Only	O
works	O
that	O
are	O
original	O
are	O
subject	O
to	O
copyright	O
protection	O
,	O
so	O
some	O
scholars	O
claim	O
that	O
machine	B-Application
translation	I-Application
results	O
are	O
not	O
entitled	O
to	O
copyright	O
protection	O
because	O
MT	O
does	O
not	O
involve	O
creativity	O
.	O
</s>
