STANDARDS FOR COMMUNICATION AND E-LEARNING IN
VIRTUAL WORLDS
The Multilingual-assisted Chat Interface
Samuel Cruz-Lara, Tarik Osswald, Jordan Guinaud, Nadia Bellalem and Lotfi Bellalem
LORIA / INRIA Nancy - Grand Est, 615 Rue du Jardin Botanique, 54600 Villers-l
`
es-Nancy, France
Keywords:
Multilinguality, MLIF, Chat interface, Web services, Communication, e-Learning, Automatic translation, Vir-
tual worlds.
Abstract:
Many of today’s applications embed textual chat interfaces or work with multilingual textual information.
The Multilingual Information Framework (MLIF) [ISO DIS 24616] is being designed in order to fulfill the
multilingual needs of today’s applications. Within our research activity for the MLIF standard, we developed
the Multilingual-Assisted Chat Interface, which intends to help people communicate in virtual worlds with
others who do not speak the same language and to offer new possibilities for learning foreign languages.
By developing this application, we also wanted to show the advantages of using web services for externalizing
computation: we used the same web service for two virtual worlds: Second Life and Solipsis.
In this paper, we first propose a short analysis of social interactions and language learning in virtual
worlds. Then, we describe in a technical way the features, architecture and development indications for the
Multilingual-Assisted Chat Interface.
1 INTRODUCTION
Today, talking to people via a textual chat interface
has become very usual. Many web applications have
an embedded chat interface, with a varying array of
features, so that the users can communicate from
within these applications. A chat interface is also easy
to implement: unlike voice or video, it needs neither
additional devices nor additional signal analysis al-
gorithms. Therefore it is not surprising if brand new
technologies such as virtual worlds also embed a tex-
tual chat interface.
But all applications have their own peculiarities,
and their chats also serve various requirements. A
distinctive feature of virtual worlds is that people are
more likely to converse with other people who can-
not speak their native language. In such cases, the
need for some sort of assistance in facilitating inter-
language communication becomes obvious. A chat
interface with multilingual features can meet these
requirements.(Cruz-Lara et al., 2009). Moreover,
such an interface can be turned into an advantage for
people who want to improve their foreign language
skills in virtual life situations.
In this paper, we first want to present some con-
siderations about social interactions and language
learning in virtual worlds. Then, we will de-
scribe chat interfaces in general and more specifi-
cally the Multilingual-Assisted Chat Interface, which
we have developed within the ITEA2 Metaverse1
(www.metaverse1.org) Project [ITEA2 07016] in or-
der to give a first answer to the question “how can
we ease communication in virtual worlds and turn the
multilinguality issue into an advantage?”
2 SOCIAL INTERACTIONS
The social interaction in virtual worlds constitutes a
particularly rich field of research. Indeed, the ob-
jective to be reached is to offer simple and effective
means of communication, which approach the nat-
ural communication. In this context, efforts should
be made as much in improving the technical aspects
as in taking into account the socio-cognitive aspects.
Thus, it will improve the realism of the virtual envi-
ronments and increase the quality of the exchanges
between the avatars. Therefore, gestures, speech, di-
rection of gaze, postures or facial expressions have an
entire role in the construction of the social links be-
tween individuals.
The question concerning the influence of virtual
45
Cruz-Lara S., Osswald T., Guinaud J., Bellalem N. and Bellalem L. (2010).
STANDARDS FOR COMMUNICATION AND E-LEARNING IN VIRTUALWORLDS - The Multilingual-assisted Chat Interface.
In Proceedings of the 12th International Conference on Enterprise Information Systems - Human-Computer Interaction, pages 45-52
DOI: 10.5220/0002894800450052
Copyright
c
SciTePress
environments on the social behaviour of users, con-
stitutes a particularly interesting topic for the re-
searchers in sociology. In fact, they highlighted a phe-
nomenon of disinhibition and facilitation which leads
to a greater sociability (Suler, 2004)(Coleman, 2007).
As social human beings, we adjust our behaviour with
the social norms in face to face communication. We
know, thanks to our education and our culture, what is
socially acceptable or not. Communicating by inter-
posed computers strongly decreases this adjustment
because we cannot observe in real-time the effects of
our words and of our writings.
In order to propose credible and powerful commu-
nication between avatars, the characteristics of the hu-
man communication must be taken into account: lan-
guage with explicit or implicit references to the ob-
jects of the environment, gestures, postures, facial ex-
pressions. These elements of communication are all
the more important since the avatar is immersed in
a three-dimensional world populated by objects, per-
sonages and places more or less characteristic which
sometimes echoes the real world.
The models suggested by El Jed (El Jed et al.,
2006) try to take into account intentional communica-
tion as well as non-intentional communication in the
interpretation of the acts of communication between
avatars. In this context, the favoured mode of com-
munication is natural language combined with deic-
tic gestures. The difficulty, in this case, consists in
using markers like vocal intensity, voice intonation,
or indexical or deictic references (“I”, “here”, “over
there”) associated with the designation gesture to de-
termine the relevant interpretation of the exchanges.
The direction of the gaze can also be exploited in
order to focus the visual attention of the interlocu-
tors towards a specific place in the shared environ-
ment. The facial expressions are essential during the
exchanges and constitute the first channel to commu-
nicate emotions. They can express mood, approval or
disapproval, but also the whole panel of the human
emotions (fear, joy, etc.). All these manifestations of
the human communication would be very useful in
the domain of education, specially for the develop-
ment of e-learning techniques used for the realisation
of virtual campuses (De Lucia et al., 2009).
3 LANGUAGE LEARNING
Language learning in virtual worlds is a new field of
research which is still open to innovations. How can
we create technological advances in order to create
an optimal psycholinguistic environment for language
learning? What makes new proposals innovative and
helpful? In order to answer these questions we are
currently developing some empirical support.
We believe that one potential source of guidance
may be offered by some methodological principles
of Task-Based Language Teaching (TBLT) applied
to distance foreign language teaching (Doughty and
Long, 2003). It should be noted that the TBLT as-
pect of our work is currently under development.
The general idea is allowing teachers to create TBLT
units via the Moodle learning environment system
(http://www.moodle.org), and then to use SLoodle
(http://www.sloodle.org). SLoodle is an open source
project which integrates Moodle components in Sec-
ond Life.
Our approach (i.e., the Multilingual-Assisted Chat
Interface) must be considered as an innovative form of
Computer-Assisted Language Learning (CALL).
4 THE MULTILINGUAL
ASSISTED CHAT INTERFACE
The Multilingual-Assisted Chat Interface is a tool of-
fering new functionalities to the chat users in Virtual
worlds. It is directly embedded in some virtual worlds
viewers (to date: Second Life and Solipsis).
In order to implement those functionalities (de-
scribed in Section 4.2), we modified the source code
of the viewers (see Section 4.5).
The Multilingual-Assisted Chat Interface mainly
relies on the Multilingual Information Framework
(Cruz-Lara et al., nd), which is a standard being cur-
rently developed by the International Organization for
Standardization (ISO).
4.1 Generalities about Chat Interfaces
The term “chat” refers to a real-time written dialogue,
using a computer. The chat presents many similarities
with the oral dialogue. In fact, it surely is the written
means of communication which is the closest to it.
Indeed, it is closer than other tools, such as forums
and email.
Most of the time (for example in Second Life), the
chat is volatile. In fact, the contents of a chat session,
like an oral conversation, is not intended to be avail-
able to the public. Furthermore, when a user logs in,
he totally ignores what has been said before his ar-
rival. Similarly he cannot know what will be said after
his disconnection. Moreover, the chat users introduce
into their writing some elements which are specific to
oral communication.
The chat is usually based on a client-server archi-
tecture, meaning that users do not communicate di-
ICEIS 2010 - 12th International Conference on Enterprise Information Systems
46
rectly with each other, but through a single server. All
the chat users connected to one server do not necessar-
ily communicate together. In general, a server gives
access to several channels of discussion (also known
as rooms), which are completely partitioned. The chat
users only see what is happening in the channel they
are connected to, and they can only send messages to
this very one. On most of the public servers, the cre-
ation of channels is completely free, and any user can
open some.
In general, the client chat interface is split into
three areas:
the ongoing conversation;
the message editing and sending zone;
the listing of the connected users.
A chat session can be considered as a set of mes-
sages, ordered sequentially and produced by various
authors, humans or robots.
4.2 Functionalities
In this section, we are going to describe the three
main functionalities which we implemented in the
Multilingual-Assisted Chat Interface.
4.2.1 Grammatical Analysis and Word
Colouring
This is the first feature that we implemented. It con-
sists in coloring some specific words in a sentence
written in the chat interface, in order to show the
grammatical structure of the sentence more clearly.
The settings can be modified in a specific menu: the
user can choose which grammatical categories they
want to highlight, and the corresponding color. They
can also choose which sentences they want to analyze
(other people’s sentences, objects’ sentences, all the
sentences, etc.).
The grammatical part-of-speech analysis is per-
formed on a remote web server, using the method de-
scribed in Section 4.4. The data structure used for tag-
ging the grammatical category of each word is MLIF.
4.2.2 Providing Word Translations, Synonyms
and Definitions
An important feature is the ability to simply click on
a word in the chat interface in order to get defini-
tions, synonyms and/or translations of this word. In
the current implementation, the definitions and syn-
onyms are retrieved from WordNet, and the transla-
tions from Google Translate. It is important to note
that other external corpora could also be used.
This feature could be needed in two main situations:
When people are reading text in a language they
do not know very well, they may need some help
(e.g. definitions, synonyms, translations) in order
to understand even very common topics.
When the discussion is about a rather precise sub-
ject, where several technical terms are often used,
people may especially need additional definitions
even if they are native speakers.
The obvious advantage of this feature is that it is
able to aggregate information from several web ser-
vices in just one click, which is much more con-
venient than looking for the information in a web
browser by oneself. Figure 1 shows the menu, the
chat interface (with the verbs in a different colour)
and the action performed when clicking on a word.
Every MLIF data structure generated after click-
ing on a word can be stored in a database. Doing so
provides the user with a feedback on the words that
he did not understand that well. Writing down the
unknown vocabulary is something very usual when
learning a new language and this is exactly what we
have implemented here.
4.2.3 Automatic Translation
When people do not know a language very well, they
will be interested in having an automatic translation
of every sentence. In this case, it is no longer an e-
learning functionality but a way to make communica-
tion easier between people in the virtual worlds.
For example, user A uses the Multilingual-
Assisted Chat Interface and wants to have all the mes-
sages displayed in French. The Multilingual-Assisted
Chat Interface will analyse the incoming messages
and translate them if they are not written in French
(using Google Translate). Then, the messages sent
by user A will be translated with respect to the lan-
guage of the latest received message in the conversa-
tion. Figure 2 shows a typical situation involving two
avatars who neither understand nor speak the same
language.
Another important point is that the source lan-
guage is automatically detected by Google Translate.
Thus, the user only needs to enable the automatic
translation functionality to be able to chat with any
other avatar in the virtual world. Also, as the source
language is stored in the MLIF data, it is possible to
link every discussion to a pair of languages and as a
consequence, it is possible to carry out several multi-
lingual conversations at the same time.
In addition to that, both messages are stored as
MLIF data. Thus, the user can click on one translated
STANDARDS FOR COMMUNICATION AND E-LEARNING IN VIRTUALWORLDS - The Multilingual-assisted Chat
Interface
47
Figure 1: Colouring words in the chat interface and displaying information about one word (Solipsis).
Figure 2: Automatic translation between a Japanese and a French avatar.
ICEIS 2010 - 12th International Conference on Enterprise Information Systems
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sentence and see the original sentence if they want
some insight into the original language or if the trans-
lation does not seem very accurate.
4.3 General Architecture
Figure 3 shows the general high-level architecture of
the main components of the Multilingual Assisted
Chat Interface.
Three colors are used in this scheme. Each one
represents a certain category of components:
orange (on the left): components belonging to the
virtual world (especially the viewer);
blue (in the middle): the web service components
that we developed, mainly business components;
green (on the right): external web services and cor-
pora, and data storage.
The circled numbers represent the chronological
order of the interactions between the components
when a message is sent or when a word is clicked.
The corresponding explanations are written below:
1. Every message sent by a user is first sent to the vir-
tual world server. When the client (i.e. the viewer)
of the person we are writing to receives a message,
this is forwarded to a Message Manager, (i.e. the
component set dealing with the chat messages).
We needed to modify these components both in
Snowglobe (a viewer for Second Life, see Sec-
tion 4.5.1) and in Solipsis.
2. Before displaying the message on the
Chat Interface, the Message Manager sends
an HTTP request to the web service (the
Grammatical Analyser) in order to obtain the
MLIF data representing the sentence and its
several grammatical components.
3. The Grammatical Analyser connects to external
Grammatical Corpora in order to get the gram-
matical part-of-speech tag for each word of the
message.
4. When the Message Manager receives the MLIF
data structure representing the original message
with a grammatical labeling (as an HTTP re-
sponse), the MLIF data is parsed and turned into
a format enabling the coloring and hyper linking
of each word. The coloring code depends on the
settings of the user interface (see Section 4.2.1).
5. An action is performed: while the addressee reads
the message, they click on a word that they do
not understand (in the Chat Interface) in order to
retrieve synonyms, definitions and translations for
this word.
6. After clicking on the word, the user is redirected
to a Web Interface, which will display all the de-
sired information.
7. Loading the web page involves calling the
Word Request Manager so that it retrieves infor-
mation from external web services.
8. First, the Word Request Manager retrieves some
definitions and synonyms from WordNet.
9. Second, the Word Request Manager connects to
Google Translate in order to retrieve translations.
10. Once the Word Request Manager has received all
the desired information, all of it is written into an
MLIF data structure. This MLIF data is stored in
a database, from which it can be retrieved later if
required (see Section 4.2.2).
11. The MLIF data is then sent to an
MLIF-to-HTML Parser, which is going to
transform the MLIF data into user-friendly
HTML code.
12. The HTML code thus obtained is finally displayed
by the Web Interface user interface, which makes
it easy for the user to read.
It is important to note that most data exchanges are
made using MLIF, since this data format exactly fits
our requirements. This is very important to facilitate
the development within the web service (as we only
use one data format) and for future applications (as it
enhances interoperability).
4.4 Web Services for Virtual Worlds
The Multilingual-Assisted Chat Interface is based on
a web service. While the virtual world client viewer is
in charge of displaying information, the web service
deals with data processing.
The text is sent by the viewer (Second Life, Solip-
sis, etc.) to the web service. The latter gathers the in-
formation requested by the users and puts it together
into a MLIF data structure. Finally, the generated
MLIF data is returned to the viewer, which turns it
into a displayable format.
The web service has a grammatical tagger tool
(Brill, 1992). It is composed of two Python-generated
dictionaries: a default tag dictionary and a rule dictio-
nary. The first one contributes to the matching of each
word with its most likely category, the second one to
the correction of errors by checking the context.
Interoperability is one of the most interesting fea-
tures in our web service: we can use our web service
to build new tools on any platform (other metaverse
platforms, web services, applications, etc.). Note
that it is used both for the Multilingual-Assisted Chat
STANDARDS FOR COMMUNICATION AND E-LEARNING IN VIRTUALWORLDS - The Multilingual-assisted Chat
Interface
49
Figure 3: The Multilingual-Assisted Chat Interface flowchart.
Interface in Second life and in Solipsis. External-
izing tools on PHP servers makes them platform-
independent and saves a lot of time when applications
must be adapted to different platforms.
Many web services exist on the web and propose
specific ways to process information. Most of the
time, there are separate tools for translating, for find-
ing synonyms or for getting the definition of a word
(Google Translate, WordNet, ConceptNet, etc.). Our
web service uses all those tools in order to allow
the user to centralize all this information in only one
MLIF data structure.
4.5 Virtual Worlds Programming
The multilingual-assisted chat interface is now avail-
able in two virtual worlds: Second Life, developed by
Linden Lab, and Solipsis, developed by Orange Labs
and ArtefactO. This section describes our work in a
technical way and is therefore directed to people who
have an advanced knowledge of programming.
4.5.1 Snowglobe
Snowglobe is an alternative viewer for Second Life
that can be downloaded on the official web site at
http://snowglobeproject.org. This project aims at
gathering Linden Lab and open source developers in
order to create an innovative viewer.
The developers who want to implement new
features can get the source code on the Second Life
wiki (http://wiki.secondlife.com/). This page
contains the source code, artwork and open
source libraries for all operating systems. All
the instructions concerning compilation and pri-
vate linked libraries are detailed on the wiki
(http://wiki.secondlife.com/wiki/Snowglobe) in the
“Get source and compile” section.
We are now going to explain how to modify the
chat interface and what we have modified in order to
build the Multilingual-Assisted Chat Interface.
Modifying the Chat Interface. A user can send a
message with two kinds of tools: the public chat inter-
face and the instant messaging interface (i.e. private
messages to one specific user).
The Public Chat Interface. The text written into
the chat interface can be modified in two ways.
The first one consists in modifying the text before
sending it to the server and the second one con-
sists in modifying the text upon its reception by
the viewer.
For the first case, the code is located in the
files named llchatbar.cpp, llchatbar.h and llchat.h.
The LLChatBar class is directly linked to the
LLPanel class (defined in the files llpanel.cpp and
llpanel.h) which is in charge of displaying the
menu elements, among the chat elements. In par-
allel, the text is sent to the server from the func-
tion named send chat from viewer. This func-
tion has three parameters. The string parameter
utf8 out text is the text that the user has written.
The type parameter (of type EChatType) indicates
the range of the message. The range will depend
on whether the user wants to whisper or to shout.
It will be different too if the message concerns all
the members of a region, the owner of an object
or just a single user. The last parameter is the
channel. There are public channels and private
channels. Generally, we use private channels to
communicate with objects.
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The code for the second case is mainly defined
in the LLTextEditor class (see lltexteditor.cpp and
lltexteditor.h). Once the text has been written
by the user, received by the LLPanel class and
sent to the server by the LLChatBar class, the
LLTextEditor class deals with the next step: it pre-
pares the text for the class which is in charge of
the display.
LLTextEditor has three important functions:
appendColoredText, appendStyledText and
appendText. The appendColoredText func-
tion defines the style of the text and calls the
appendStyledText function. The latter applies
the style to the text and finds out the HTML
addresses to replace them by clickable links. If
a link is detected, a new style is defined and the
appendText function is called. When the code has
completed the analysis of the HTML links, the
appendText function is called a second time with
the previous style. Each style change requires the
appendText function to be called. In other words,
appendText can consider only one style at the
same time.
The Instant Message Interface. There is an-
other way to communicate, which allows the
user to have private communications with other
users. This means of communication is called
instant message and is defined in another file:
llimpanel.cpp. The main function is called
addHistoryLine. It can edit history and call func-
tions of the LLTextEditor class in order to write
into the instant message panel.
The Multilingual-Assisted Chat Interface. The
functions we built for the Multilingual-Assisted Chat
Interface are mainly defined in the LLTextEditor class.
When the viewer receives text, the buildMLIF
function converts it into a MLIF data structure
thanks to the web service, which provides the
grammatical category for each word. Then,
three functions (parseMLIFAndReturnCategories,
parseMLIFAndReturnLinks and
parseMLIFAndReturnWords) are called to parse
the MLIF data structure and they return respectively
each word, its grammatical category and the link to
its information.
In the following, a “grammatically tagged link”
defines a clickable HTTP link which embeds the
grammatical category information of the word. A
grammatically tagged link allows the viewer to rec-
ognize a word category and to apply it to the corre-
sponding style and URL. It is composed of a word
and its grammatical tag (tag://word). For example,
if you write the verb “be” and wish to colour it, the
viewer will create a “verb://be” grammatically tagged
link. We chose to represent the links like this for im-
plementation reasons. In fact, this was the clearest
way to enable coloration and clickability of words in
Snowglobe, since it is the same structure as the usual
“http://website” links. The main format is MLIF; the
“tag://word” is only a bridge between MLIF and the
chat interface in Snowglobe.
The addTags function matches a word with its
grammatical category in order to create a grammati-
cally tagged link and to apply the colour chosen by the
user. We have defined as many grammatically tagged
link types as there are grammatical categories.
When user A wants an instant translation in their
language of what user B says, the function buildMLIF
requests the web service to return a MLIF data struc-
ture with user B
´
ıs sentence in its original language
and the same sentence translated in user As language.
Both original and translated sentences are stored in
the MLIF data structure. Indeed, user A can consult
the original sentence if the translation is odd or if they
want to learn the other language. The MLIF data is
parsed by theparseMLIFAndReturnTranslatedWords
function, which returns translated words.
All those functions are not called at the
same time. A menu proposes several options
(see 4.2). Each option is saved in an XML file
(panel preferences linguistic chat.xml), which is
managed by the functions defined in the files
llprefslingchat.cpp, llfloaterpreference.cpp and
llstartup.cpp. The appendStyledLinguisticText
function in the LLTextEditor class can verify
if an option is activated before calling the as-
sociated function. For instance, if the variable
linguisticChatActivateInstantTranslation is ac-
tivated, the viewer will use the function which
allows an instant translation of a sentence to be
displayed(parseMlifAndReturnTranslatedWords).
4.5.2 Solipsis
Solipsis is a French virtual world (still under develop-
ment), which is notable for two features. First, it plans
to implement a decentralized Metaverse platform that
will use a peer-to-peer protocol. Second, it inte-
grates a web browser directly in the three-dimensional
space. All the objects created can embed a web
browser (as a texture applied on a surface), which
is compatible with many web technologies (Flash,
Javascript, etc.).
The Multilingual-Assisted Chat Interface on
Solipsis is roughly similar to the Snowglobe version.
The general development is typically the same but the
structure is different.
STANDARDS FOR COMMUNICATION AND E-LEARNING IN VIRTUALWORLDS - The Multilingual-assisted Chat
Interface
51
The graphical chat interface is defined in an HTML
file (uichat.html) and built with HTML and Javascript.
All the classes and functions we have described for
the Snowglobe version are written in C++ in the files
GUI Chat.cpp and GUI Chat.h.
The HTML file contains a form linked to a
Javascript function (sendMessage). This calls a C++
function of GUI chat.cpp (addText). This function
decides, with respect to the user’s preference of
whether to use the linguistic functionalities or not, to
convert the text to MLIF data or not. In other words,
it calls one of the two sending methods declared in the
HTML file:
1. sendTextMessage, which writes text into the chat
interface without data processing;
2. sendMLIFMessage, which converts MLIF data
to human-readable text (with the function
convertMlifToText), and matches the tags with
both corresponding colours and links (with the
function colorWordByTagAndMatchLink).
The menu is implemented in the HTML file
menuLinguisticChat.html and the actions that the user
can execute with the in-world interface menu are de-
clared with showMenu C++ function. When a user
clicks on a word, a new in-world web browser appears
thanks to the showBrowser C++ function.
5 CONCLUSIONS
First, we would like to highlight again that all the data
exchanges are made using MLIF, because we intend
to enhance interoperability through standardization.
We believe standardization to be a key issue in the
development and dissemination of new technologies.
Up to now, the grammatical coloration of the
words in our Multilingual-Assisted Chat Interface in-
terface is only available in English. In fact, such an
analysis has to be based on linguistic corpora and the
one we use only contains English terms. However, we
plan to adapt our technology to other analysers such
as Treetagger.
In the same way, the translations rely on the
Google Translate web application. As its quality of
translation is improving every day (thanks to its “sug-
gest” functionality), we can expect better translations
in the future.
The other important point which should be noted
is that the web service which we developed has been
used for both Second Life and Solipsis. Externalizing
applications (especially service applications) is very
useful in order to minimize the development time and
to be able to use more adapted data structures.
But the Multilingual-Assisted Chat Interface is
still a prototype. In the future, we intend to improve
the reliability of this interface. We will distribute
the modified Snowglobe viewer to a large number of
users for testing and collect feedbacks. Adding new
features to the chat interface in order to facilitate so-
cial interactions and e-learning is a process which still
requires time, research and new technologies.
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