1. Deaf Culture and Sign Language Writing System – a Database for a New
Approach to Writing System Recognition Technology
Cayley Guimarães, Jeferson F. Guardezi, Luis Eduardo Oliveira, Sueli Fernandes
Federal University of Parana - UFPR
{cayleyg, jfguardezi, lesoliveria, suelif}@inf.ufpr.br
Abstract
The Deaf have been denied their natural
language for over a hundred years, with dire
consequences for their health, citizenship and
culture. Sign Language is the natural language of the
Deaf, used for intellectual development and other
human traits that are language related. Writing
Systems (sequence of characters to represent a
language) store and retrieve information for
literature, science, knowledge creation, information
dissemination, communication over time and space
etc. SignWriting is a writing system deemed adequate
to the spatial-visual nature of Sign Languages.
However, current computational technologies fail to
provide the Deaf with effective tools for their writing
needs (they lack usability, and/or are one-to-one
translation from the oral language etc.). This article
proposes a new, more natural approach: that of
using screen and stylus for online handwritten
recognition of SignWriting. This research makes
available a database to be used by computer
vision/character recognition to inform design of
SignWriting editors.
1. Introduction
Deaf people were once considered clinically
deficient, and were subjected to procedures to
“remove” deafness in order to become “normal”. The
oral language became the de facto condition for
social acceptance [1] [2]. However, the Deaf have the
right to an identity, language and culture. They have
the right to access the available human possibilities
such as symbolic communication, social interaction,
learning, etc. Sign Language, of visual-spatial
manner, is the natural language of the Deaf, capable
of providing complex linguistic functionalities. Deaf
culture is the term applied to the social movement
that regards deafness as a difference in human
experience – rather than a deficiency [1] [2] [4].
Unfortunately, Deaf children who are born into
non-Deaf families (90% of the cases) are unable to
acquire the oral language, and they have little to no
exposure to Sign Language [1] [2]. This lack of early
language acquisition of a mother tongue causes
severe consequences to the Deaf’s intellectual
development, citizenship and culture [2]. The Deaf
do not acquire basic concepts of daily life, and,
therefore, do not develop the superior psychological
faculties, a process that is mediated by language [3].
Quality education requires language.
Additionally, it requires that children and adults be
able to use their own language within the world in
which they inhabit, both orally and written [59].
However, “many minority and indigenous people
groups do not have that opportunity – quite simply
because their language is not written down”. [59]
goes on to point out that the lack of a writing system
is another factor of marginalization, and that the use
of a writing system of the mother tongue may interact
with other factors to increase opportunities. Some of
these opportunities are literacy and education for
economic development; increased ability to learn
other languages; chance for cultural expression and
wider dissemination of cultural values – thus leading
to appreciation by others of the culture’s richness;
increased security in one’s own identity; the option to
use the language in electronic media [59]
The Deaf have difficulties to acquire a writing
system, be it of the oral language, or of the Sign
Language [1] [4]. Writing systems serve as support
for the modern, global society. They are used for
literature, cultural preservation, information storage
and retrieval, science, knowledge creation,
communication among many others many vital
societal functions [11]. Sign Languages share a
commonality with other oral languages from minority
and indigenous groups that have their own cultural
and traditional means of maintaining folk language
art forms. SignWriting, created by Sutton [4] is the
most used writing system for Sign Language. There
is very few written material in Sign Language, which
2014 47th Hawaii International Conference on System Science
978-1-4799-2504-9/14 $31.00 © 2014 IEEE
DOI 10.1109/HICSS.2014.418
3368

2. deprives the Deaf community of a major component
of their culture, education and overall development.
Exceptions can be found at [4]. It is not enough to
present the Deaf with concepts in the oral language,
and expect them to create concepts in their own
culture [60].
Current computer editors, which aim at providing
the Deaf with writing system support, fail to deliver,
either because they lack usability and/or because they
have inadequate approaches [14]. Firstly, they
provide the user with a series of menus from which to
choose the primitives of SignWriting – this approach
renders the task of writing a sign a difficult and time-
consuming process (e.g. SW-Edit [5]). Some systems
require the Deaf to wear gloves and sensors – thus
limiting their ability to utter properly in Sign
Language as in Lu, Shark, Hall & Zeshan [6]. Other
systems are a one-to-one glossary, with the input
being in the oral language – a total dependency on
the oral language and limited to the availability of the
word on the database (e.g. Delegs-Editor [7]).
Finally, they are translators – again, from the oral
language – and require extensive knowledge of
Computer Science (SWML [8]).
Computer vision is a field that has attempted to
develop services based on Sign Languages, but
mostly they concentrate on video work, and, to our
knowledge, although there are several studies of hand
writing recognition for many languages such as
Japanese, Arabic, Chinese among others, there is still
a long way to go for writing systems of Sign
Language.
The challenge to provide tools for written Sign
Language is an urgent, clear call for innovative
approach, lest we are faced with an entire community
with no written history. Memory dependent and non-
memory dependent are two different manner of
human existence, and the latter is considered to be
the basis for modern society [11] [59].
Thus, the main goal of this research is to propose
a new paradigm – that of using hand written character
recognition of SignWriting, with a broader, Human-
Computer Interaction perspective of the Deaf needs,
in a natural, more direct writing way, through the use
of a tablet screen and stylus. Simply put, the user
would “draw” the primitives of SignWriting into the
tablet using the pen, and computer vision hand
writing recognition would then generate the
appropriate sign from the handwritten input.
In order to achieve the proposed goal, Computer
Vision requires a database with which to work. This
paper presents an online database of handwritten
SignWriting primitives collected using tablets and
pen devices. Such database is to be used by the
computer vision community to inform design of
SignWriting systems. The database is available at
(address omitted for blind review). Standard database
allows the development, evaluation and comparison
of different algorithms.
The approach presented recasts computer vision
into the role of front runners in the noble task of
developing computer services for real and effective
tools for the writing needs of the Deaf; services that
should be used to inform design of artifacts for social
inclusion and cultural preservation.
The remainder of this paper further describes the
plight of the Deaf, and their need for Sign Language
and a writing system; briefly discusses SignWriting
as a writing system of choice; shows some
inadequacies of related work and, then, presents the
online database.
2. Deaf issues, Sign Language
The lack of early Sign Language acquisition (the
mother tongue of the Deaf) makes it difficult for Deaf
children to learn basic concepts of daily life [9]. The
learning of such basic daily life concepts should
occur when the child recognizes patterns in the world
and start to identify linguistic labels for them. Later,
the child learns to ask questions in order to clarify
doubts, and starts to form relations that alter their
cognitive structures: Children begin to combine,
compare, infer, deduce and extrapolate old and new
knowledge, in a mental process that is mediated by
social experiences and language [9].
This lack of mother tongue acquisition is
detrimental to the intellectual development of Deaf
children, and brings about severe consequences, such
as the inability to perform daily tasks for the
development of intelligent action; the inability to
learn and plan; the inability to overcome impulsive
behavior; the dependency on concrete, visual
situations; difficulties to control herself and to
socialize, among others [9] [10]. Thus deprived of
intellectual development and use of language,
members of the Deaf community face intellectual and
social barriers of information access and knowledge
creation, needed for identity formation and full
citizenship [10]. Additionally, the Deaf grows into a
reality where there is little written material in Sign
Language [4].
Eighty five per cent (85%) of the world
population uses some sort of Writing System, which
serves as support and basis for the modern, global
society [11] [59]. Writing systems are a sequence of
symbols that represent a language. They serve many
functions: they reproduce speech, thoughts, and
abstract concepts among other language related
3369

3. events [11]. Writing systems are more then “the
painting of the voice” as Voltaire wanted: writing
systems are a cultural representation of society, as
used in literature; they are the utmost tool of human
knowledge, necessary for science development; they
play a major role in information dissemination in
journalism; in many cultures, the calligraphy is an art
[11] [12] [13].
As for writing systems for Sign Language, several
authors claim its importance. Writing systems are
more objective and substantial than the linguistic
communication: it allows for abstract notions; and
writing systems are rooted in the fundamental human
need to store and retrieve information for
communication with others over time and space [11]
[12]. Writing systems are used to organize one’s
lives, record dreams, discoveries and feelings [13].
Writing fulfills specific functions and meanings that
require deliberate analytic actions needed to create an
intentional structure: writing conveys more than
ideas: it represents our way of seeing, feeling and
interpreting the world [14].
The new intellectual technologies brought about
by the computer should be better explored as
managers of memory; through recording of social
enunciation, and through writing systems, that allows
humanity, via writing, to keep a more permanent
history, less dependent of individual memory [15].
Writing systems are usually associated with the
oral language, and, as such, there is a misconception
about the possibilities and gains of the use of a
writing system by the Deaf, who use Sign Language.
Sign Language is a complete linguistic system, of
visual-spatial manner. Thus, Sign Language requires
a writing system that is compatible to its nature (i.e. a
writing system that is capable of mapping the visual-
spatial properties of the language that it proposes to
represent).
The use of an adequate writing system for Sign
Language helps the Deaf to develop an internal
structure akin to her natural language, in a process
that increases the linguistic and cognitive skills; such
use enhances identity and Deaf culture [16].
Unfortunately, the Deaf community had their
process of research, development and use of Sign
Language and its writing system interrupted for over
a hundred (100) years by the International
Conference of Deaf Educators, whose delegates
banned the use of Sign Language in Deaf education
[1] [2] [4] [13] [14]. This lack of access to an
adequate language and writing system deprived the
Deaf of meaning construction and educational
learning strategies. The use of the writing system
from the oral language, of which the Deaf have little
to no understanding, doesn’t aid the learning,
memorization, association of knowledge, access to
knowledge of other related areas [14]. The
advantages that reading and writing could offer will
exist only if the linguistic code used is naturally
accessible – that is, a writing system of Sign
Language [14].
There are co-existing proposed writing systems
for Sign Language, of which the following are some
examples: Mimographie notation by Bébian [17];
Stokoe notation [18]; Hamburg Notation System –
HamNoSys by Hanke [19]; D’Sign system by
Jouison [20]; François Neve notation [21]; and
SignWriting [4]; some are restricted to the Brazilian
Sign Language, such as Elis [22] and SEL [23]. The
fact that there are many conflicting writing systems
alone is, per se, a complicating factor. SignWriting is
universal, and it is the most used writing system in
Brazil and in the world [25], and, therefore, shall be
the focus of this study.
3. Importance of a writing system for Sign
Languages
Language is more than a way of communication
[24]. Language includes a regulation function of
thought [3]. [14] presents a literature review of some
of the existing writing systems for transcription of
signs, such as the notations from Stokoe, François
Neve, HamNoSys and SignWriting. These notations
are writing systems for signs, developed to facilitate
the recording and registration of signs through
graphical symbols.
SignWriting is the most used writing system for
Sign Language [25]. It is universal (i.e., just like the
Latin alphabet is used by many writing system,
SignWriting is used by many different Sign
Languages). SignWriting is based on a
pictorial/ideographic representation system, whose
organizing principle follows visual-spatial significant
elements [4]. It is a system conceived to be used by
Deaf people in their daily tasks. It serves the same
purposes as other writing systems from oral
languages: take notes, read and write books and
newspaper, learning at school, write contracts, do
research, create literature etc.), thus making it
valuable in real practical use [4] [14].
Figure 1 presents some Signs in American Sign
Language (ASL), and its written form in SignWriting,
Stokoe’s notations and HamNoSys. The Signs are for
the English words “What”, “Quote”, “Three”,
“Bears” and “Goldilocks”.
3370

4. Figure 1 – Examples of different writing systems
for American Sign Language. Source [14]
The incorporation of the writing system of the
Sign Language (i.e. SignWriting) into the political-
pedagogical projects developed in a bilingual context
for the Deaf represent a paramount contribution to
the dissemination of the Libras and of the Deaf
culture. Such incorporation constitutes a mediating
tool for Bilingual Literacy of the Deaf. Bilingual
literacy, the adequate choice for Deaf education [24],
is the resulting process of social practices of the use
of the written form as a symbolic system [24]. Sign
Language is to be acquired by the Deaf via a
functional use of the language, where language
assumes a character of real meaning: “Therefore,
Literacy as effective appropriation is pleasurable, is
leisure, is access to information, is communication, is
a way to exercise citizenship in different social
practices” [1:131].
From the point of view of the linguistic political
planning, the use of the semiotic writing system
legitimates the representation of the Deaf culture, as
well as the identity ties, given the important role that
the dissemination of a writing system takes on the
standardization, lexical enhancement and overall
literary and artistic accumulation [1] [59]. In such
political and social scenario, a more natural use and
dissemination of SignWriting creates the opportunity
for a greater balance in power relations between the
Sign Language and the oral language (Portuguese, in
our case). Sign Languages increase in importance due
to the historical role of writing systems in
maintaining alive the memory of the language. This
memory is achieved by the incorporation and
recording of the collection of human knowledge. The
information culture aims at the construction of a
collective intelligence, which, among other
processes, is achieved through language. The goal is
to educate citizens in the storage, retrieval, evaluation
and effective use of information to solve problems
and make decisions [26]. The exclusion of the Deaf
implicates in their non-participation in this
construction of intelligence.
From the pedagogical point of view, the current
discussion is related to the specificities of the
alphabetization of the Deaf, and how the SignWriting
should constitute a mediating element in the
appropriation of the alphabetic writing system of the
oral language [4] [14]. The learning of the oral
language by the Deaf works with the premise that
meaning attribution in writing follows from visual
and symbolic processes, in which the use of Sign
Language takes on a pivotal role. The written form of
the second language can be achieve because the
development of writing is independent from the oral
language, given that it is a different system, both in
structure and behavior [3].
However, to realize such premise, there is a need
for educational processes that differ from the ones
used in teaching the oral language as the maternal
language (for non-Deaf children). The current
methods do not scaffold the learning by the Deaf, and
it takes approximately nine (9) years to alphabetize a
Deaf child [23]. Alphabetization relies on the
relations between phoneme and graphemes made by
the native speakers, which cannot be achieved by the
Deaf. Some studies about the specificities of the
literacy process of the Deaf [1] [16] [24] [27] address
such issue by proposing to forgo the domain of the
relations letter-sound as a premise to access the
writing system.
[1] [24] and others propose the use of Sign
Language as a mediating symbolism in the learning
of the written text, and the use of methodological
processes from the teaching of a second language to
foreigners to enable the insertion of the Deaf in
literacy practices. To read without being
“alphabetized” corresponds to the reality of subjects
that possess a non-alphabetic language as the mother
tongue, and said subjects master the writing systems
of a second alphabetic language, even if they do not
communicate orally through it [1]. In this sense, the
direct visual aspect of SignWriting represents a
mediator element that contributes to the development
of the complex superior psychological functions (e.g.
memory, abstraction, generalization, meta-language
etc. [3]) of the Deaf children, in a manner that
increases literacy.
3371

5. Existing editors are detrimental to the teaching
and use of SignWriting. Consider, if you will, a
scenario where a Deaf is watching a class, and wants
to take her own notes: such simple task would be
time and effort consuming if she were to use such
editors [4] [14].
The present research proposes a more natural way
to enter text in SignWriting: hand-written character
recognition of SignWriting using a tablet and a stylus.
This is an innovative intermediary process in the
acquisition of SignWriting. Such approach serves as
mediation for the acquisition of both the writing
system of the Sign Language and of the oral
language. It allows for the establishment of new
relations for knowledge creation and new forms of
mental activities, cognitive development, historical
vector of standardization and cultural support. The
database presented is to inform design of systems that
support this direct approach.
4. SignWriting: writing system for Sign
Languages
Sign Languages are consisted of several
parameters such as Hand Configuration, Contact
(Location), Palm of Hand Orientation, Global and
Local Movement and Non-Manual Expressions [18].
Linguists use such phonological parameters to
describe a sign in Sign Language. Several
computational models have been created to represent
them [28]. Devised by Valerie Sutton [4] in the mid-
70’s, SignWriting has been the most universally
accepted and used writing system for Sign Languages
around the world [13] [25]. The reader can find
several learning materials for SignWriting [4] [13]
[25].
According to International SignWriting Alphabet
(ISWA) [29], there are 30 pictorial symbol groups.
Each group contains 639 basic pictorial symbols. It is
possible for each basic symbol to have 96 variations
(up to 6 different fills and 16 rotations). Such
combinations yield a total of 35,023 valid symbols.
These numbers have increased with the ISWA 2010.
A much longer time is therefore needed to select and
combine symbols to input a single sign than to type a
word. The few existing editors for SignWriting are
not complete; they lack usability resources; they are
not in SL (i.e. they are in the oral language), they use
specific, sophisticated software interaction (e.g. many
levels of a menu to find a primitive) etc., all of which
render them difficult to use, and they exclude the
context of natural writing by the Deaf [13] [14] [22]
[23].
SignWriting preserves the tridimensional
characteristics of the Sign Language as it
contemplates several representations for the
phonological parameters, such as: Hand position and
orientation; Types of Contacts; Hand Configuration;
Finger Movements; Arm Movements and Pointing;
Non-Manual Expression; Facial Expressions;
Location of Symbols in the Head; Head Movement;
Gaze orientation; Body Movement; Movement
Dynamics, among others. Figure 2 shows a picture of
a Hand Configuration in three orientations and its
representation in SignWriting.
Hand Configuration is one of the basic
SignWriting primitives for a hand configuration in
three different orientations. Some of the symbols
used by SignWriting are very iconic, which allows for
a rapid association with the actual sign. The
graphemes are presented simultaneously and
sequentially, in a manner that best suit the nature of
the Sign Language – a considerable difference when
compared to other writing systems, which present the
graphemes in linear form, in a pattern that follows the
logic of the alphabetic writing of the oral languages.
Figure 2 – Hand Configuration and the
corresponding SignWriting. Source [4].
5. Automatic Sign Language recognition
Albeit the several positive aspects related to
accessibility and inclusion that the systematization
and dissemination of a writing system in Sign
Language would bring to the Deaf community, there
are very few publications, and the informational tools
in SignWriting are precarious. The editors for
SignWriting can be thus classified: First we have the
“drag and drop” paradigm [5] [30] in which the user
is presented with a series of menus she must navigate
to find the desired SignWriting primitive, drag it to
the “writing” area, and repeat the navigation process
3372

6. until she finds all the primitives she wants (out of at
least 35,000 primitives). Then, she is left with the
task of trying to place the primitives on the correct
location in an attempt to form the desired sign, with
little to no usability and accessibility support.
Some editors require the user to wear
cumbersome accessories, such as gloves, sensors etc.
Others [7] are one-to-one translation from the oral
language: this requires the Deaf to have extensive
knowledge of the oral language (which is often not
the case). Additionally, Sign Language is a
completely different language, not dependent on the
oral language, which makes such translation not
viable. But the worst problem with the systems that
follow such paradigm is that this approach allows for
the writing of only the words that are present in the
editor’s database (e.g. COFFEE may be in the
database, but, if CAFETERIA isn’t already stored in
the editor, then the user won’t be able to generate the
SignWriting). Additionally, the surveyed editors did
not allow the user to enter her own signs. Lastly,
there are highly computational mark-up languages
(SWML) [8], which are not adequate for general use.
They would be more adequate for an actual
translator: but that still will be more suited for non-
Deaf people, who would be required to know before
hand the entry to such translator (usually, the oral
language, or some sort of video recognition).
Research in SL automatic recognition began in
the late 80´s [31]. Since then, the field has seen
innumerous studies in an attempt to recognize signs
from video that were very successful in their
mathematical, computational, and algorithmic
approaches, but they have yet to deliver technological
artifacts that promote effective interaction in
situations of real use in SignWriting.
Most studies are for video Sign Language speech
recognition [32] [33] [34]. Some studies are for
gesture recognition [35]. Other studies are limited by
a one-to-one lexical approach [36], by the use of only
finger spelling, instead of real signs. [37] presents a
comprehensive overview of available language
resources for Sign Language processing and
recognition.
[6] presents a system developed for recognition of
hand movements. However, the proposed system
uses video and glove, and the resulting use is that of
mimicking the writing “in the air” to be captured by
cameras. That would be the equivalent of requiring
the user to wear a glove in her tongue for speech
recognition systems. [38] proposes to recognize
simulation of SignWriting with cameras, where the
hand is tracked across the video using a computer
vision algorithm. These approaches are far from the
actual natural writing of SignWriting. Additionally,
they may present problems with occlusion and loss of
hand position, high computational cost and non-
practical results.
As for handwriting character recognition, much
work has been done on the recognition of Latin
characters, covering both the cases of separated (hand
printed) characters and cursive script. Several
databases for English off-line handwriting
recognition are summarized in [39] [40]. Some
researches have been done on the task of recognizing
other writing systems, such as the Arabic characters
[41] [42] [43]; Indian characters [44]; Japanese Kanji
[45]; Korean [46]; Chinese [47] [48]; Farsi [49]; [50]
for Indonesian off-line character recognition used for
the Latin script of the Indonesian language; Urdu
(51) and so on. For other domains, we can cite bank
cheques [52], postal address [53], and even shapes
[54] among others.
Unfortunately, to our knowledge, there isn’t a
database of handwritten SignWriting available for
online recognition.
The handwriting systems discussed above assume
that the handwritten word is already segmented into
separated characters before recognition; the training
and testing data consisted of only a small number of
samples written by a single writer. They lack
generalization, and present low recognition
accuracies. Additionally, they are usually for off-line
handwriting character recognition. Off-line character
recognition works with static information that is
acquired after all the text is written. Online character
recognition works with information on the dynamics
of the writing process as the text is being written.
[55] presents a database that uses electronic pen
on digital tablet for online handwritten Tibetan
character recognition. [56] presents a process for data
acquisition, processing and feature extraction for
Urdu characters, but fail to provide a public database
with which the community can work to design the
required software.
The literature review shows a picture that calls for
challenging the traditional assumptions and
perspectives that strongly frame the computer
vision´s efforts. In Human-Computer Interaction, the
human side is the most valuable, the most demanding
and expensive part of the equation. Technology
should serve humans, and not the other way around:
humans should not have to “adapt” themselves in
order to be able to use technology. Human-Computer
Interaction field has long established the notion that
the observation and understanding of what people do
is no longer enough. Design and technology should
be engaged in meeting societal challenges [57].
Conceptually, the picture shown by the related work
depicts some (miss) conceptions on how the design
3373

7. object is being framed; on how the stakeholders
(users) are viewed; on the underlying assumptions
being made in the user’s name; on the validity of
such assumptions; on the lack of new ways to
characterize the deaf problems, etc.
6. SignWriting hand recognition
Character recognition consists mostly of
converting images of handwritten text to text in
editable form. However, due to the SignWriting’s
large set of characters, a more natural approach is
necessary. There are several technologies that use
touchscreen and stylus, and some quite accurate
programs are available for input of geometric forms,
numbers, mathematical symbols, English, Japanese,
Chinese and Latin characters, among others.
But, to our knowledge, there is no support for
SignWriting. Successful SignWriting handwritten
character recognition is a complex process comprised
of several steps that are interdependent. There is a
need for a standard database of images to inform
research in handwritten SignWriting text recognition.
Such database should be used in the development,
evaluation, and comparison of different, specific
algorithms [40].
Most existing handwriting recognition algorithms
can not be directly use for SignWriting recognition:
for example, the recognition of Japanese writing is
made easier because the writing in Japanese follows a
prescribed order in which the word should be written.
SignWriting does not provide such facilitator.
This research advances the state of the art by
proposing a new SignWriting paradigm – one in
which the user writes in a tablet with touch-screen
and a stylus. The first step to achieve such goal is to
generate corpus with which computer handwritten
recognition should work, focus of this research.
The database presented is an ongoing project: it is
our goal to make it available, so that others can
enhance it by adding source material, as well as use it
to create specific handwriting recognition algorithms.
Data was collected assuming that handwritten varies
due to knowledge of SignWriting, technology, age,
sex and different date/time.
In its current form, it contains written material
from 37 instances of the 118 hand configurations for
the Brazilian Sign Language [13]. That is: each
subject wrote the 118 primitives on a touch screen
with stylus tablet. Each subject used the data
collecting system at least twice. Figure 3 presents a
print screen of the data colleting system. As can be
seen, the system presents the symbol, and provides a
free area for the user to reproduce such symbol.
Figure 3 – Data collecting system.
The subject can erase and correct her writing, and
save when she is done. Figure 4 presents a sample of
the data collected.
Figure 4 – Sample of the collected primitives.
Table 1 presents information about the 8 Deaf
subjects, who knew SignWriting.
Table 1 – Deaf subject information.
Initials Gender Age # of
Uses
MVV Female 27 2
STT Female 19 2
NC Female 25 2
LS Female 33 1
AMF Female 45 2
CMD Female 35 2
BPMS Female 26 2
FHP Male 34 2
Table two presents information about non-Deaf
subjects who did not know SignWriting.
3374

8. Table 2 – Non-Deaf subject information.
Initials Gender Age # of
Uses
LRK Male 08 1
BYJ Female 08 1
RF Male 20 2
AFJ Male 23 2
DD Female 25 2
CS Female 25 2
VHS Male 23 2
DS Male 25 3
NJS Female 20 3
AW Female 45 3
CG Male 42 3
Both AMF and AW are left-handed. Figure 5
illustrates the use of the tablet to write in
SignWriting.
Figure 5 – Direct writing.
The shape of a character varies from person to
person, and for the same person, from time of
collection to the next. Writers provide the samples in
the writing area in successively manner, with no
constraints regarding the quality of the drawing.
The choice to start working with hand
configuration was based on the fact that most signs
have at least one hand configuration. The sample
includes various instances of each group of the
SignWriting hand configuration.
During the collection of data, the subjects
volunteered some inputs that validated the proposal.
These inputs are summarized here as per the
categories proposed by [58]: Response: The Deaf
subjects immediately demonstrated their approval of
the new paradigm. Non-Deaf subjects were happy to
find out that Sign Languages have a writing system.
Motivation: The subjects expressed gladness to be
able to collaborate with the research. Reflection:
Non-Deaf subjects constantly inquired about the
actual hand configuration, and asked for examples of
a sign using the hand configuration. Deaf subjects
questioned each and every hand configuration,
exemplifying with signs. In one instance, the Deaf
said that a specific hand configuration did not exist,
because they were not able to find a sign using it. The
researchers went back to [13], and found out that said
hand configuration is both a hand configuration, and
a sign for network MODEM. As it turned out, the
questioning resulted in the Deaf learning a new sign.
10. Discussions
Not every language has a writing system, but,
historically, all languages that use some sort of
writing system are richer: users of writing systems
are less dependent on oral history. A writing system
for Sign Languages contributes for the Deaf
community overall memory, literature, scientific
knowledge creation, note taking, communication
among others. Existing editors for Sign Language are
inadequate.
This position paper proposes a more natural way
to use one of the Sign Language writing system: that
of writing directly on a device. The use of the
proposed paradigm empowers members of the Deaf
community with tools to appropriate their written
system: in order to preserve their culture, language,
history, knowledge creation, and literature, among
others. Specially, it provides the Deaf with means to
become less dependent of the Sign Language
utterances only.
It is all belief that researchers will find this new
paradigm worth the while. The database will be a
useful tool in their work on SignWriting recognition.
This ongoing research is already working on:
enhancing the database with more collections;
enhancing the database with other categories of
SignWriting, such as primitives for movement,
location among other parameters of Sign Languages.
The research group is also working on the design of a
text editor for SignWriting. Most importantly, the
group is working on devising algorithms to enable
hand written recognition.
11. References
[1] Fernandes, S., Educação dos Surdos, IBPEX, Curitiba,
2012.
[2] Skliar, C., Atualidade de educação bilíngue para
Surdos, Mediação, Porto Alegre, 1999.
3375

9. [3] Vigotsky, L.S., Mind in society: the development of
higher psychological processes, Harvard University Press,
Boston, MA, 1974.
[4] Sutton, V., Lessons in SignWriting, La Jolla, CA,
available
http://www.signwriting.org/archive/docs4/sw0354-US-
SWLiteracyProject-2006.pdf Accessed at 02/21/2013.
[5] SW-Edit. Available at http://www.signwriting.org
Accessed at 02/21/2013.
[6] G. Lu, L-K. Shark, G. Hall, U. Zeshan, “Hand motion
recognition and visualization for direct sign writing”, IEEE,
DOI 10.1109/IV.2010.71, 2010, pp. 467-272.
[7] Delegs-Editor, available at http://www.delegs.com
accessed in 02/19/2013.
[8] A.C.R. Costa, G.P. Dimuro, “A SignWriting-Based
Approach to Sign Language Processing”, LNCS, v. 2298 p.
202-205, 2002.
[9] MacNamara, J., Names for things: a study of human
learning. The MIT Press, Cambridge, MA, 1982.
[10] J. Kyle, “Beginning Bilingualism”, Ibero-American
congress on bilingual education, Lisbon, 2005.
[11] Fischer, S.R., A history of writing, Reaktion Books,
NY, 2009.
[12] Martin, H.-J., The history and power of writing,
Chicago, Banton, 1994.
[13] Barreto, M., Barreto, R., Escrita de sinais sem
mistérios. Ed. do Autor, BH, 2012.
[14] Stumpf, M.R., Aprendizagem de escrita de língua de
sinais pelo sistema SignWriting, Ph.D. Thesis, UFRGS,
Porto Alegre, 2005.
[15] Lévy, P., Cyberculture. Odile Jacob, Paris, 1999.
[16] Capovilla, F.C., Raphael, W.D., Dicionário
enciclopédico ilustrado trilíngue da língua de sinais
brasileira, Edusp, São Paulo, 2001.
[17] Bébian, R.C. Mimographie, or essai d’écriture
mimique. Paris, 1825. Available at http://www.cultura-
sorda.eu/resources/Bebian_mimographie/1825.pdf
Accessed in 02/19/2013.
[18] Stokoe, W.C., Sign Language structure, Linstok Press,
Silver Spring, 1960.
[19] Hanke, T., HamNoSys: representing sign language
data in language resources and language processing
contexts. In:: O. Streiter, C. Vettori (Eds.), LREC’04:
Representation and processing of sign languages, ELRA,
Paris, 2004.
[20] Jouison, P., Écrits sur la langue des signes française.
Harmattan, Paris, 1995.
[21] F.-X., Neve, “Phonologie or gestematique des langue
de signes des sourd”, Linguistic and Language Behaviour
Abstracts, v.26, I, 3-4, p. 1954-1964.
[22] Barros, M.E., ELIS, Ph.D. Thesis, UFSC,
Florianópolis, 2008.
[23] A.S.C., Lessa-de-Oliveira, “Libras escrita”, ReVel,
v.10, n.19, available at http://revel.inf.br Accessed in
02/19/2013.
[24] Sánchez, C. La educación de los sordos en um modelo
bilíngue, Diakona, Mérida, 1991.
[25] I. Roald, “Teng Skrift: innforing I tegnskrift. Bergen:
Vestlandet Kompetansesenter. Available at
http://www.signwriting.org/archive/ Accessed in
02/19/2013.
[26] M.J. Menou, “Cultura, informação e educação dos
profissionais de informação nos países em
desenvolvimento”, Ciência da Informação, Brasília, V.25,
n.3.
[27] Hoffmeister, R., Famílias, crianças surdas, o mundo
dos surdos e os profissionais de audiologia, In: C. Skliar
(Org.) Atualidade da educação bilíngue para surdos.
Mediação, Porto Alegre, 1999.
[28] Guimarães et al., “Structure of the Brazilian Sign
Language (Libras) for computational tools: citizenship and
social inclusion. In: M.D. Lytras et al. (Eds.), WSKS,
Corfu, Greece, CCIS.XXVII, p.110-120. ISBN 978-3-642-
16323-4.
[29] ISWA, 2008, Available at http://www.signwriting.org
Accessed in 02/19/2013.
[30] C.S. Bianchini, F. Borgia, M. de Marsico, “Swift – a
signwriting editor to bridge between deaf world and e-
learning”, ICALT, IEEE, 2012, p.526-530. DOI
10.1109/ICALT.2012.235
[31] M.P. Paulraj, “A phoneme based sign language
recognition system using skin color segmentation”, 6th
CSPA, p.1-5, 2010.
[32] P. Dreuw, D. Stein, H. Ney, “Enhancing a sign
language translation system with vision-based features”, In:
Intl. Workshop on Gesture in HCI and Simulation”, Lisbon,
2007.
[33] P. Dreuw et al., “Benchmark databases for video-
based automatic sign language recognition”, Available at
http://www.vu.edu/asllrp/cslgr Accessed at 02/19/2013.
[34] C. Vogler, D. Metaxas, “A framework for recognizing
the simultaneous aspects of ASL”, Computer Vision &
Image Understanding, v.81, n.3, p.358-384, 2001.
[35] T.S. Huang, Y. Wu, “Vision-based gesture
recognition: a review”, Gesture Workshop, France, v.1739
of LNCSS, p.103-115, 1999.
[36] R. Bowden et al., “A linguistic feature vector for the
visual interpretation of sign language”, European Conf.
Computer vision. V.1, p.390-401, 2004.
[37] B.L. Loeding et al., “Progress in automated computer
recognition of sign language”, In: K. Miesenberger et al.
(Eds.), ICCHP LNCS 3118, p.1079-1087. 2004.
[38] J. Rett, S. Luis, J. Dias, “Laban movement analysis for
multi-ocular systems”, IEEE/RSL Intl. Conf. on Intelligent
Robots and Systems, p.22-26, 2008.
[39] C.Y.Suen, “At the frontiers of OCR”, IEEE, v.7,
p.1093-1100, 1992.
[40] U.V. Marti, H. Bunke, “A full English sentence
database for off-line handwriting recognition”, Proc. of the
5th
Intl. Conf. on Document Analysis and Recognition,
p.705-708. 1999.
[41] S. Al-Ma’adeed, D. Elliman, C.A. Higgins, “A
database for Arabic handwritten text recognition research”,
IEEE/IWFHR, 0-7695-1692-0/02, 02.
[42] H. Alamri et al., “A novel comprehensive database for
Arabic off-line handwriting recognition, 11th
ICFHR, 2008.
[43] F. Slimane et al., “A new Arabic printed text image
database and evaluation protocols”, 11th
ICDAR, p.946-
950, 2009.
[44] U. Bhattacharya, B.B. Chaudhuri, “Databases for
research on recognition of handwritten characters of Indian
scripts”, 8th
ICDAR, p.789-793, 2008.
3376

10. [45] W. Zhang et al., “Using combined Gradient and
Wavelet Feature”, Guangzhou, DOI
10.1109/ICCIAS.2006.294218, p.662-667, 2006.
[46] D.-H. Kim et al., “Handwritten Korean character
image databes PE92”, IEICE Trasn. Information and
systems, E79-D(7): 943-950, 1996.
[47] H.G. Zhang et al., “HCL2000 – a large-scale
handwritten Chinese character database for handwritten
character recognition”, 11th
ICDAR, p.286-290, 2009.
[48] T.H. Su, T.W. Zhang, D.J. Guan, “Corpus-base HIT-
MW database for offline recognition of general-purpose
Chinese handwrittern”, Int. J. Document Analysis and
Recognition, 10(1), p. 27-38, 2007.
[49] M. Ziaratban, K. Faez, F. Bagheri, “FHT – A
unconstraint Farsi handwritten text database, 11th
ICDAR,
p. 281-285, 2009.
[50] P.R. Aryan et al., “Development of Indonesian
handwritten text database for offline character recognition”,
Bandung, p.1-4, DOI 10.1109/ICEEI.2001.6021582, 2011.
[51] I. Haider, K.U., “Online Recognition of single stroke
handwritten Urdu characters”, IEEE 978-1-4244-4873-9,
2009.
[52] C.O. Freitas et al., “Brazilian bank check handwritten
legal amount”, XIII SIBGRAPHI, 2000.
[53] M.Y. Chen, A. Kundu, J. Zhou, “Off-line handwritten
word recognition using HMM type stochastic network”,
IEEE Transactions on Pattern Analysis and Machine
Intelligence, v.15, n.5, p.481-496, 1994.
[54] B. Serge, J. Malik, J. Puzicha, “Shape Matching and
Object Recognition Using Shape Contexts”, IEEE
Transactions on Pattern Analysis and Machine Intelligence,
v.24, n.24, p.509-522, 2002.
[55] L.-L., Ma, H.-D. Liu, J. Wu, “MRG-OHTC database
for online handwritten Tibetan character recognition”,
IEEE Intl. Conf. on Document Analysis and Recognition,
p.207-211, 2011.
[56] K.U. Khan, I. Haider, “Online recognition of multi-
stroke handwritten Urdu characters”, IEEE 978-1-4244-
5555-3/10, 2010.
[57] Carroll, J.M., Human-Computer Interaction in the
New Millennium, Addison-Wesley Professional, 2001.
[58] Flood, C.M., How do Deaf and hard of hearing
students experience learning to write using SignWriting, a
way to read and write signs?, Ph.D. Thesis, The University
of New Mexico, 2002.
[59] UNESCO. Mother Tongue Day - languages and
writing. Available at
http://portal.unesco.org/education/en/ev.php-
URL_ID=28301&URL_DO=DO_TOPIC&
URL_SECTION=201.html Accessed 02/19/2013.
[60] R. Jonhson, S. Liddell, C. Erting, “Unlocking the
curriculum: Principles for achieving access in Deaf
education”. Gallaudet University Research Institute, DC,
1989.
3377