EXPERIENCES WITH AN ON-LINE TRANSLATING 
DIALOGUE SYSTEM 
Seiji MHKE, Koichi HASEBE, Harold SOMERS , Shin-ya AMANO 
Research and Development Center 
Toshiba Corporation 
1, Komukai Toshiba-cho, Saiwai-ku 
Kawasaki-City, Kanagawa, 210 Japan 
ABSTRACT 
An English-Japanese bi-directional machine 
translation system was connected to a keyboard 
conversation function on a workstation, and tested 
via a satellite link with users in Japan and 
Switzerland. The set-up is described, and some 
informal observations on the nature of the bilin- 
gual dialogues reported. 
INTRODUCTION 
We have been developing an English-Japanese 
bi-directional machine translation system imple- 
mented on a workstation (Amano 1986, Amano et 
a/. 1987). The system, which is interactive and 
designed for use by a translator, normally runs in 
an interactive mode, and includes a number of spe- 
cial bilingual editing functions. We recently real- 
ized a real-time on-line communication system 
with an automatic translation function by combin- 
ing a non-imeractive version of our Machine Trans- 
lation system with the keyboard conversation func- 
tion just like talk in UNIX**. Using this system, 
bilingual conversations were held between mem- 
bers of our laboratory in Japan and visitors to the 
5th World Telecommunications Exhibition Tele- 
corn 87, organized by the International Telecom- 
munication Union, held in Geneva from 20th to 
27th October 1987. 
In the fh-st part of this paper, we discuss in 
detail the configuration of this system, and give 
some indications of its performance. In the second 
part, we report informally on what for us was an 
interesting aspect of the experiment, namely the 
nature of the dialogues held using the system. In 
*the Centre for Computational Linguistics, 
University of Manchester Institute of Science and 
Technology, England 
**UNIX is a trademark of AT&T Bell Labora- 
tories. 
particular we were struck by the amount of meta- 
dialogue, i.e. dialogue discussing the previous 
interchanges: since contributions to the conversa- 
tion were being translated, this metadialogue 
posed certain problems which we think are of gen- 
eral interest. In future systems of a similar 
nature, we feel there is a need for users to be 
briefly trained in certain conventions regarding 
metadialogue, and typical system translation 
errors. Furthermore, an environment which mini- 
mizes such errors is desirable and the system must 
be 'tuned' to make translations appropriate to con- 
versation. 
SYSTEM CONFIGURATION 
A general idea of the system is illustrated in 
Figure 1. Workstations were situated in Japan and 
Switzerland, and linked by a conventional satel- 
lite telephone connection. The workstations at 
either end were AS3260C machines. Running 
UNIX, they support the Toshiba Machine Transla- 
tion system AS-TRANSAC. On this occasion, the 
Machine Translation capability was installed only 
at the Japanese end, though in practice both termi- 
nals could run AS-TRANSAC. 
The workstation screens are divided into three 
windows, as shown in Figure 2, not unlike in the 
normal version of UNIX's talk. The top window 
shows the user's dialogue, the middle window the 
correspondenfs replies. The important difference 
is that both sides of the dialogue are displayed in 
the language appropriate to the location of the ter- 
minal. However, in a third small window, a 
workspace at the bottom of the screen, the raw 
input is also displayed. (This access to the English 
input at the Japanese end is significant in the case 
of Japanese users having some knowledge of 
English, and of course vice versa if appropriate.) 
The bottom window also served the purpose of 
indicating to the users that their conversation part- 
ners were transmitting. 
155 
OIALOGUE 
USING 
KEYOOARO$ 
svalze~ 
Figure 1. General Set-up 
tel lo, Takeda. My name is suzanne. 
\[ live in geneva, but I come froe California. 
/es, ~t ~hen I ~as 12 ~ars old. 
/ery interesting, Quick, and useful ! 
~ov many languages do you spaak, Takeda ? 
rhet is ok. \] 
=- __'L., ........ --:_._-'- II MY name is Takeda. 
Please tell me your name. 
Where do YOU live? 
\]see. 
Have you visited Japan? 
Please tell me the impression of this machir 
Thank you. 
I can speak only Japanese. 
IS \[l\[liil~ : SUZLHIII,C't,~qVI 
I1 Ill=ill Iil\]lll',,,i~ilBI g IIIl~i\] 
Switzerland 
/~-, Tal<eclao ~o)~l~l:s u zanne~o 
~v,, ----b~,b/~'~J 2~'~'~o 
~o k~1"o 
That is ok, 
Figure 2. Screen Display 
Japan 
156 
Figure 3 shows the set-up in more detail. At 
the Japanese end, the user inputs Japanese at the 
keyboard, which is displayed in the upper window 
of the workstation screen. The input is passed to 
the translation system and the English output, 
along with the original input is then transmitted 
via telecommunications links (KDD's Venus-P and 
the Swiss PTT's Telepac in this case) to Switzer- 
land. There it is processed by the keyboard conver- 
sation function, which displays the original input 
in the workspace at the bottom of the screen, and 
the translated message in the middle window on 
the screen. The set-up at the Swiss end is similar 
to that at the Japanese end, with the important 
exception that only the original input message is 
transmitted, since the translation will take place 
at the receiving end. 
TRANSLATION METHOD 
An input sentence is translated by morphologi- 
cal analyzer, dictionary look-up module, parser, 
semantic analyzer, and target sentence generator. 
Introducing a full-fledged semantic analyzer con- 
flicts with avoiding increases in processing time 
and memory use. To resolve this conflict, a Lexi- 
cal Transition Network Grammar (LTNG) has 
been developed for this system. 
LTNG provides a semantic framework for an 
MT system, at the same time satisfying processing 
time and memory requirements. Its main role is to 
separate parsing from semantic analysis, i.e., to 
make these processes independent of each other. In 
LTNG, parsing includes no semantic analysis. Any 
ambiguities in an input sentence remain in the syn- 
tactic structure of the sentence until processed by 
the semantic analyzer. Semantic analysis proceeds 
according to a lexical grammar consisting of rules 
for converting syntactic structures into semantic 
structures. These rules are specific to words in a 
pre-eompiled lexicon. The lexicon consists of one 
hundred thousand entries for both English and 
Japanese. 
SYSTEM PERFORMANCE 
Once the connection has been established, con- 
versation proceeds as in UNIX's talk. An impor- 
tant feature of the function is that conversers do 
not have to take turns or wait for each other to 
finish typing before replying, unlike with write. 
This has a significant effect on conversational 
strategy, and occasionally leads to disjointed con- 
versations, both in monolingual and bilingual dia- 
logues. For example, a user might start to reply 
to a message the content of which can be predicted 
after the first few words are typed in; or one user 
might start to change the topic of conversation 
while the other is still typing a reply. 
Transmission of input via the satellite was gen- 
erally fast enough not to be a problem: the real 
bottle-neck was the physical act of input. Novice 
users do not attain high speed or accuracy, a prob- 
lem exacerbated at the Swiss end by a slow screen 
echo. But the problem is even greater for Japanese 
input: users typed either in romaji (i.e. using a 
standard transcription into the Roman alphabet) 
or in hiragana (i.e. using Japanese-syllable values 
for the keys). In either case, conversion into kanji 
(Chinese characters) is necessary (see Kawada et 
al. 1979 and Mori et al. 1983 on kana.to-kanji 
conversion); and this conversion is needed for 
between a third and a half of the input, on average 
(el. Hayashi 1982:211). Because of the large hum- 
AS 3260C 
E2 conversation I 
_~ function 
El.,, 
r2.,E2 
PTT 
Telep~ 
"J2,E2 
KDD E2 
Venus-P Jr 
3260C 
\ 
I conversation 
function 
translation 
system 
Switzerland 
Figure 3. Configuration 
Japan 
157 
ber of homophones in Japanese, this can slow 
down the speed of input considerably. For exam- 
ple, even for professional typists, an input speed 
of 100 characters (including conversions) per 
minute is considered reasonable (compare expected 
speeds of up to 100 words/minute for English typ- 
ing). It is of interest to note that this kana-to- 
kanji conversion, which is accepted as a normal 
part of Japanese word-processor usage, is in fact a 
natural form of pre-editing, given that it serves as 
a partial disambiguation of the input. 
On the other hand, slow typing speeds are also 
encountered for English input, one side-effect of 
which is the use of abbreviations and shorthand. 
In fact, we did not encounter this phenomenon in 
Geneva, though in practice sessions (with native 
English speakers) in Japan, this had been quite 
common. Examples included contractions (e.g. 
pls for please,.u for you, cn for can), omis- 
sions of apostrophes (e.g. cant, wont, dont) 
and non-capitalization (e.g. i, tokyo, jal). 
The translation time itself did not cause signif- 
icant delays compared to the input time, thanks to 
a very fast parsing algorithm, which is described 
elsewhere (Nogami et al. 1988). Input sentences 
were typically rather short (English five to ten 
words, Japanese around 20 characters), and transla- 
tion was generally about 0.7 seconds per word 
(5000 words/hour). Given users' typing speed and 
the knowledge that the dialogue was being trans- 
mitted half way around the world, what would, 
under other circumstances, be an unacceptably long 
delay of about 15 seconds (for translation and 
transmission) was generally quite tolerable, 
because users could observe in the third window 
that the correspondent was inputting something, 
even if it could not read. 
TRANSLATION QUALITY 
This environment was a good practical test of 
our Machine Translation system, given that many 
of the users had little or no knowledge of the tar- 
get language: the effectiveness of the translation 
could be judged by the extent to which communi- 
cation was possible. Having said this, it should 
also be remarked that the Japanese-English half of 
the bilingual translation system is still in the 
experimental stage and so translations in this 
direction were not always of a quality comparable 
to those in the other direction. To offset this, the 
users at the Japanese end, who were mainly 
researchers at our laboratory and therefore famil- 
iar with some of the problems of Machine Transla- 
tion, generally tried to avoid using difficult con- 
structions, and tried to 'assist' the system in some 
other ways, notably by including subject and 
object pronouns which might otherwise have been 
omitted in more natural language. 
We recognized that the translation of certain 
phrases in the context of a dialogue might be dif- 
ferent from their translation under normal circum- 
stances. For example, Engfish I see should be 
translated as naruhodo rather than watashi ga 
miru, Japanese wakarimashita should be I under- 
stand rather than I have understood, and so on. 
Nevertheless, the variety of such conversational 
fillers is so wide that we inevitably could not 
foresee them all. 
The English-Japanese translation was of a high 
quality, except of course where the users - being 
inexperienced and often non-native speakers of 
English - n~de typing mistakes, e.g. (I). (In 
these and subsequent examples, E: indicates 
English input, J: Japanese input, and T: transla- 
tion. Translations into Japanese are not shown. 
Typing errors and mistranslations are of course 
reproduced from the original transmission.) 
(la) E: this moming i came fro st. galle to 
vizite the exosition. 
E: it is vwery inyteresti ng to see so 
many apparates here. 
(lb) E: 
(lc) E: 
J: 
J: 
I arderd "today's menu'. 
i would go tolike a girl. 
b~ 9 "~-¢A,o 
T: I don't understand. 
t o 1 i k e ~j:fSJ'C"~';~o 
T: What is tolike? 
These were sometimes compounded by the 
delay in screen echo of input characters, as in 
example (2). 
(2) E: Sometimes, I chanteh the topic, 
suddenly. 
E: I change teh topic. 
J: ~ ~ ~o 
T:I understand. 
E: I had many mistakes. 
J: ~b ~ ~: I¢~-C v-,'£ ~o 
T: Are you tired? 
E: A little. 
E: But the main reason is the delay fo 
dispaying. 
E: But the main reason is the delay of 
display. 
158 
Failure to identify proper names or acronyms 
often led to errors (by the system) or misunder- 
standings (by the correspondent), as in (3a), espe- 
cially when the form not to be translated happens 
to be identical to a known word, as in (3b). In 
(3b), 'go men na sai' means in Japanese that I'm 
sorry. 
(3a) E: lars engvall. 
J: 1at s engva 1 lhtfaJ" 
"O3'-~0 
T: What is lars engvall? 
E: this is my name. 
(3b) \[having been asked if he knows 
Japanese\] 
E: How about go men na sai? 
T: &'©,,t: 5 Ir__Ic.-9 v-,-C~ <_ 
Jk_n a_ s a i. 
This was avoided on the Japanese-English side 
where proper names were typed in romaji (4). 
(4) J: ~I,©~--~I~N o g a m i "C'"J-o 
T: My name is Nogami. 
As with any system, there were a number of 
occasions when the translation was too literal, 
though even these were often successfully under- 
stood (5). 
(5) E: 
J: 
Do you want something to drink? 
~o 
T: Yes. 
E: What drink do you want? 
J: ~w= -- e -- ~JJC~.3.h: w, 
T: I want to drink a warm coffee. 
E: warm coffee? 
E: Not a hot one? 
J: ,,~, v, = -- e --'e3"o 
T: It is a hot coffee. 
One problem was that the system must always 
give some output, even when it cannot analyse the 
input correcdy: in this environment failure to 
give some result is simply unacceptable. Howev- 
er, this is difficult when the input contains an 
unknown word, especially when the source lan- 
guage is Japanese and the unknown word is trans- 
mitted as a kanji. Our example (6) nevertheless 
shows how a cooperative user will make the most 
of the output. Here, the non-translation of tsuki 
mae (fi\] ~ ) is compounded by its mis-translation 
as a prepositional object. The first Japanese sen- 
tence said that I married two months ago. But the 
English correspondent imagines the untranslated 
kanji might mean 'wives'! 
(6) J: ~/,t-J:27J ~ E~ L too 
T: I married to 2 ~ ~-~\]. 
E: are married to 2 what???. 
J: ~-~©6~ tc~ l.fco 
T: I married in this year June. 
E: now i understand. 
E: i thought you married 2 women. 
In the reverse direction, the problem is less 
acute, since most Japanese users can at least read 
Roman characters, even if they do not understand 
them (7): this led in this case to an interesting 
metadialogue. Again, the English user was cooper- 
ative, and rephrased what he wanted to say in a 
way that the system could translate correcdy. 
(7) E: can you give me a crash course in 
japanese?. 
J: c r a s h c o u r s e~f~'O~ 
~o 
T: What is crash course? 
E: it means learn much in a very short 
time. 
Mistransladons were a major source of metadi- 
alogue, to be discussed below, though see particu- 
larly example (10). 
THE NATURE OF THE DIALOGUES 
There has been some interesting research recent- 
ly (at ATR in Osaka) into the nature of keyboard 
dialogues (Arita et aL 1987; Iida 1987) mainly 
aimed at comparing telephone and keyboard conver- 
sions. They have concluded that keyboard has the 
same fundamental conversational features as tele- 
phone conversation, notwithstanding the differ- 
ences between written and spoken language. No 
mention is made of what we are calling here meta- 
dialogue, though it should be remembered that our 
dialogues are quite different from those reported 
by the ATR researchers in that we had a transla- 
tion system as an intermediary. No comparable 
experiment is known to us, so it is difficult to 
find a yardstick against which to assess our find- 
ings. 
Regarding the subject matter of our dialogues, 
this was of a very general nature, often about the 
local situation (time, weather), the dialogue part- 
ner (name, marital status, interests) or about 
recent news. A lot of the dialogue actually con- 
cemed the system itself, or the conversation. An 
159 
obvious example of this would be a request to 
rephrase in the case of mistranslation, as we have 
seen in (6) above, though not all users seemed to 
understand the necessity of this tactic (8). 
(8) E: how does your sistem work please. 
J: ~.L~ ~: ©~©,~b~ r) ~-'~-A,o 
T: I don't understand a meaning 
of the sentence. 
E: how does your sistem work? 
Often, a user would seek clarification of a mis- 
or un-translated word as in (9), or (3) above. 
(9) E: I could have riz in the dinner. 
J: r i z ~7 ~ :/:~-@~o 
T: Is riz French? 
E: May be. I'm not sure. 
J: ~-(" 3",~o 
T: Is it rice? 
E: In my guess, you are right. 
J: ~ ~'9"o 
T: It is natural. 
E: What is natural? 
T: I understand French. 
J: r i z ~:~'C~o 
T: Riz is rice. 
The most interesting metadialogues however 
occurred when users failed to distinguish cited 
words - a problem linguists are familiar with - 
for example by quotation marks: these would then 
be re-translated, sometimes leading to further 
confusion (10). 
0o) Jl: B~:©Ep~'~L."C < ~ Wo 
T: Please speak a Japanese 
impression. 
E1 : ichibana. 
J2: b~ ~ ",~ ~-A,o 
J3: i c h i b a n a ~1~'~';~o 
T:What is ichibana? 
E2: i thought it means number one. 
J4: f~ ~--~:'(-~o 
T:What is the first? 
E3: the translation to you was 
incorrect. 
This example may need explanation. First the 
translation of the Japanese question (J1) has been 
misunderstood: the translation should have been 
'Please give me your impressions of Japan', but the 
English user (E-user) has understood Japanese to 
mean 'Japanese language'. That is, E-user has under- 
stood J1 to be saying 'Please speak an impressive 
Japanese word.' Then E-user confused ichiban 
('number 1' or 'the first') and ikebana ('flower 
arranging'). The word ichibana (El) does not 
exist in Japanese. His explanation 'number one' 
was correctly translated (not shown here) as 
ichiban. But not realizing of course that the mean- 
ing of his first sentence (J1) was incorrectly 
understood, the Japanese user (J-user) could not 
understand E1 (J2) and asked for its sense (J3). 
So E-user tried to explain the meaning of 
/¢h/bana, which in fact was ichiban. By the 
answer, J-user has identified what E-user ment, 
but since J-user still did not realized that his first 
sentence was incorrectly understood and hence J- 
user has understood E2 to be saying that some- 
thing was 'number 1', he tried to ask what was 
'number 1' (J4). 
But in the translation of this question, ichiban 
(--~ ) was translated as 'the fLrsf. At this point, 
it is not clear which comment E-user is referring 
to in E3, but anyway, not realizing what answer 
J-user have expected and not knowing enough 
Japanese to realize what has happened - i.e. the 
connection between 'number one' and 'the firsf - E- 
user gives up and changes the subject. If E-user 
had intended to speak ikebana and explained its 
meaning, J-user could have realized J1 had been 
misunderstood. Because it is meaningless in a sen- 
tence saying someone's impression that something 
is ikebana. 
On the other hand, where the user knew a lit- 
de of the foreign language (typically the Japanese 
user knowing English rather than vice versa), such 
a misunderstanding could be quickly dealt with 
(11). 
(11) E: How is the weathere in Tokyo? 
J:we a t h e r e i'~we a t h e r 
T: Is weathere weather? 
CONCLUSIONS 
There are a number of things to be learnt from 
this experiment, even if it was not in fact set up 
to elicit information of this kind. Clearly, typing 
errors are a huge source of problems, so an envi- 
ronment which minimizes these is highly desir- 
able. Two obvious features of such an environment 
are fast screen echo, and delete and back-space keys 
which work in a predictable manner in relation to 
what is seen on the screen. For the correction of 
typing errors, the system should have a spelling- 
160 
check function which works word-by-word as 
users are typing in. The main reasons for syntax 
errors are ellipsis and unknown words. Therefore, 
the system should have a rapid syntax-check func- 
tion which can work before transmission or trans- 
lation and can indicate to users that there is a syn- 
tax error so that users can edit the input sentence 
or reenter the correct sentence. These are in them- 
selves not new ideas, of course (e.g. Kay 1980 and 
others). 
Conventions for citing forms not to be trans- 
law, d, especially in metadialogue, must be devel- 
oped, and the Machine Translation system must be 
sensitive to these. The system must be 'tuned' in 
other ways to make translations appropriate to 
conversation, in particular in the translation of 
conversational fillers like I see and wakarimashita. 
Finally, it seems to be desirable that users be 
trained briefly, not only to learn these conven- 
tions, but also so that they understand the limits 
of the system, and the kind of errors that get pro- 
duced, especially since these are rather different 
from the errors occasionally produced by human 
translators or people conversing in a foreign lan- 
guage that they know only partially. 
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APPENDIX A. 
Overall Performance Data 
sessions 78 times 
utterances 1429 times (100%) 
18.3 time/session 
utterances that were 
successfully translated 1289 times (90%) 
utterances that were 
mis-translated 140 times (10%) 
metadialogues 31 times 
0.4 time/session 
161 
APPENDIX B. 
Subject Matter in Utterances 
total utterances 
greeting and self introduction 
response signals 
about weather 
about time 
others 
1429 times (100%) 
470 times (33%) 
154 times (11%) 
92 times (6%) 
56 times (4%) 
657 times (46%) 
APPENDIX C. 
Type of Expressions in Metadialogue 
total metadialogues 31 times 
repetition of a part of partner's 
utterances (e.g. What is ichibana?) 22 times 
(English users' are 2 and Japanese users' are 20) 
telling typing errors or mistranslations 
(e.g. Error in Translation.) 9 times 
(English users' are 6 and Japanese users' are 3) 
APPENDIX D. Distribution of Utterances 
(ia), (lb), (2) and so on are corresponding to examples in the text. Those 
numbers are put in the area in which main utterances in the examples are involved. 
::,,  i!iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii!iiiiiiiiiiiiiiiiiiiiiill iiiiiiiii!iiii 
® 
: total 1429 utterances 
I' 
: 1289 utterances that were successfully translated 
: 140 utterances that were mis-~ranslated 
: 31 utterances that caused metadialogues 
A: by typing errors (7times) 
B: by mistranslations (5times) 
C: by unknown words to the partner and so on (19times) 
162 
