=Paper=
{{Paper
|id=Vol-2386/paper23
|storemode=property
|title=Information and Technology Support for the Training of Visually Impaired People
|pdfUrl=https://ceur-ws.org/Vol-2386/paper23.pdf
|volume=Vol-2386
|authors=Nataliia Veretennikova,Oleksandr Lozytskyi,Roman Vaskiv,Oksana Kunanets,Andrii Leheza,Olga Lozynska,Nataliia Kunanets
|dblpUrl=https://dblp.org/rec/conf/momlet/VeretennikovaLV19
}}
==Information and Technology Support for the Training of Visually Impaired People==
https://ceur-ws.org/Vol-2386/paper23.pdf
Information and Technology Support for the Training of
Visually Impaired People
Nataliia Veretennikova1[0000-0001-9564-4084], Oleksandr Lozytskyi1[0000-0001-8395-8385], Ro-
man Vaskiv2[0000-0002-8549-5035], Oksana Kunanets1[0000-0001-8626-9016], Andrii Leheza3[0000-
0002-8892-2426]
, Olga Lozynska1[0000-0002-5079-0544], Nataliia Kunanets1[0000-0003-3007-2462]
1Information Systems and Networks Department, Lviv Polytechnic National University, Lviv,
Ukraine
2Tech StartUp School, Lviv Polytechnic National University, Lviv, Ukraine
3Software Supply Systems Department, Uzhhorod National University, Uzhhorod, Ukraine
nataver19@gmail.com, Oleksandr.A.Lozytskyy@lpnu.ua,
vaskivroman@gmail.com, oksanka.kun@gmail.com,
andrewlegeza@gmail.com, Olha.V.Lozynska@lpnu.ua,
nek.lviv@gmail.com
Abstract. There are a lot of scientists who investigate the problem of infor-
mation accessibility for visually impaired and totally blind people. Considerable
contribution to the creation of information technologies for blind people was
made in Sweden, Japan, Germany, USA, France, Canada, Denmark, Great Brit-
ain and other leading countries. Unlike the leading countries in Ukraine the in-
formation accessibility for blind remains problematic and painful. Solving this
problem will help blind people to realize themselves in everyday life.
The paper is devoted to solving the actual scientific problem of information
availability for people with visual impairments by developing new methods and
tools for computer processing and data presentation. The authors presented the
developed software system for adapting Ukrainian-language technical texts to
people with visual impairments. This system consists of a set of processing and
conversion methods for automatic reading mathematical formulas and symbols
written in a variety of formats in Ukrainian.
As a result, a program of dubbing mathematical formulas «MathPlay» was
developed, which showed overall good results of user understanding at the
hearing voiced formulas of different complexity that estimates near 92.5%.
The obtained results can provide the basis for the development of various
training programs, practical courses and workouts of blind people working with
the computer, as well as for university education.
Keywords: Ukrainian technical text processing, visual impairment, syntax tree,
sounding, automation equipped working place, DAISY format, markup language
MathML.
1 Іntroduction
Today, there are many pedagogical, programmed and technical means for facilitating
the training of people with visual impairments, but further development in this direc-
tion is impossible without computer presentation and adaptation of teaching materials
to the needs of people with visual impairment.
People with visual impairments are constantly confronted with difficulties in the
implementation of their rights. They are deprived of an opportunity to receive infor-
mation in a natural way, since they are not able to provide themselves properly with
the necessary information resources. For example, Braille books or literature in audio
formats, not to mention special adaptations for work with computer and Internet ac-
cess.
Unfortunately, the problem of supporting schools for blind people with didactic
materials and tiflotechnic equipment has intensified. The issue of personnel training
and support is no less problematic. In special boarding schools there are not enough
teachers who have a technique of teaching and educating children with deep visual
impairment. Since the system of training such teachers is practically not developed in
our country, people who have never worked with blind children come to work in our
schools, and this often leads to negative consequences.
The use of modern information technology to provide information to blind people
is an urgent problem, the solution of which has found new approaches [1, 2].
Modern computer tools are capable of not only converting digital data into a con-
venient audio channel or dotted Braille font for the blind, but also provide the blind
with a complete computerized workplace with all the opportunities, from work in text
editors to access to the Internet or mastering suitable programming languages. Digital
Talking Book, covering both audio and text data, are invaluable multimedia infor-
mation resources for visually impaired people [3].
2 DAISY Book as a Tool of the Learning Process
NIMAS (National Instructional Materials Accessibility Standard) is a technical stand-
ard used by book publishers to create XML source files that can be used to develop
some specialized formats, for example, for Braille font or audiobooks [4].
Output files are created using the XML markup language to mark up the input con-
tent structure; they provide content representation in various forms and styles. For
example, XML files and source image files can be used not only for print products,
but also for Braille fonts, font size, HTML pages, audio files, DAISY readable books,
or with the help of a speech synthesizer, etc.
Adaptation of information resources for people with special needs to the educa-
tional needs is most appropriate with the use of the format called DAISY.
The DAISY standard, developed by the American National Institute of Standards
and the ANSI / NISO National Standards Organization, sets specifications for digital
books for people with complete or partial loss of vision, people with disabilities or
other physical disabilities that make reading difficult [5].
The main developer of this standard is the DAISY Consortium, which interacted
with a number of professional and civic organizations and formed the conceptual
framework of the standard in close cooperation with leading staff of a number of li-
braries, scientists and user-practitioners. The science and technology innovation were
directed to the main target group of vision-impaired users and users with other physi-
cal disabilities. The DAISY book is multimedia content with synchronization of text,
audio and graphic information as well as advanced features for flexible navigation in
it [6].
3 Methods and Algorithm for Creating DAISY Books that
“Speak” in Ukrainian
As a result of the pilot studies, two methods for creating DAISY “talking” books have
been identified and adapted to the Ukrainian language, with the development of the
classification of types of books and electronic documents.
The first method consists in reading the Ukrainian-language printed material into a
microphone with the subsequent processing of the received audio recording. The sec-
ond method is to maximize the automation of the process of creating a book, includ-
ing dubbing of created text files using the synthesizer of the Ukrainian language, as
well as the transformation and dubbing of mathematical formulas and graphic objects.
As a result, audio records of all parts of the book that are imported into the PRS Pro
program are mounted to create the ultimate DAISY book [7].
Then step by step it is described the method of constructing the DAISY book in
accordance with the proposed methods.
Step 1: Analysis and classification of input data (the method of classification of
documents is used).
Step 2: Defining the book structure and overlaying navigation (it is used the key-
word search method and the decision tree method).
Step 3: Finding the most important information in the book using special words
(hybrid methods and keyword search method are used).
Step 4: Searching for mathematical formulas in the text of the book (using the de-
cision tree method and keyword search method). This process becomes quite hard-
working, if the formulas in the graph formats are appearing in the book.
Step 5: Creating a text file describing the formula in the Ukrainian language and
its sounding by the language synthesizer (the method of transforming the syntactic
tree and the method of synthesis of the sound are used). As a result, we get audio files
in MP3 or WAV format.
Step 6: Building the book's current files. At this stage, the software is used to build
DAISY books, according to the needs of the developer.
In Fig. 1 it is presented a flow-chart of an audiobook content formation algorithm,
in accordance with the developed applied software system. The input file is a text or
graphic file, then the program initializes the input file format, determines the optimal
method for creating a book and issues the corresponding message to the user (if the
format of the input document is different from HTML / XHTML). The next step is to
find the most important information in the book by special words or fragments of the
text that will be dubbed by the voice of another speaker. At this stage, the hybrid
methods and the keyword search method are used. Then the transformation of the
mathematical formulas into the text description and distribution of the book into sepa-
rate parts according to the navigation parameters are performed. The result is a plural-
ity of output text or audio files for import into the DAISY PRS Pro program.
Fig. 1. Flow-chart of the DAISY book creation algorithm
The developed algorithm for creating DAISY books allowed to automate the process
of building a “talking” book in Ukrainian. In particular, it has ensured the support of
Ukrainian-language technical texts and highlighting the most important information in
the book.
4 Technologies for Transformation and Representation of
Mathematical Formulas
For the organization of the educational process in the natural sciences, books with a
formulaic component are required. For the transfer of mathematical expressions in
books created in the DAISY format, the mathematical markup language MathML is
used which is an XML element and is designed for use in XHTML documents [8, 9,
10].
Documents using the MathML language are not directly reproduced by the syn-
thesizer. For the correct reproduction of such documents, various means are used to
create different mathematical notations and text descriptions in different languages
(except of Ukrainian). Most DAISY format playback players use the notation
LAMBDA, LaTeX and Nemeth [11].
Stages of Ukrainian-language technical texts processing:
• formula scanning;
• the formula recognition and transformation into the mathematical markup
language MathML (Infty Reader, GrindEQ Math Utilities, Teacode Latex,
MathType, TeX etc. [12, 13]);
• text forming for voice (MathPlay);
• sounding the formula in Ukrainian ("Ukrainian voice UkrVox - Igor") [14].
Our developed technology allows us to convert mathematical formulas of different
complexity to the form which can further be expressed by the Ukrainian language
synthesizer. In the process of automated recording over information content, there are
problems associated with the transformation and presentation of mathematical formu-
las.
In our study, for the internal formulation of formulas, we use the MathML
language because of its prevalence, tree structure and the availability of converting
formulas, written in different formats to the MathML language. The MathML lan-
guage is selected as an intermediate one for the development of means for sounding
formulas [16-19].
For the transformation of the mathematical formulas presented in various versions
of the MathML (presentation and semantic) record, a special system of rules has been
developed for the text in Ukrainian. The system consists of rules for writing mathe-
matical symbols, operators, general and specified expressions.
Rules for specified expressions are necessary in cases when the reading result de-
pends not only on the tree node, but also on the value of its descendant. For example,
should be read the “x square”, and not “x in power two”. The rules are designed so
that the original text could be read with the synthesizer of the Ukrainian language [9].
Fig. 2. The process of sounding mathematical formulas in Ukrainian
The tools for converting mathematical formulas recorded in various formats and
the MathPlay program are the basis of an applied program system for processing
Ukrainian-language technical texts (Fig. 2) and provide a reliable and rapid solution
to a group of tasks, such as the transformation of mathematical formulas available in
linear text, to the language MathML, the analysis of mathematical formulas in relation
to the phonetic and grammatical features of the Ukrainian language, the automatic
creation of audio files with Ukrainian-language content, etc.
The developed software and algorithmic means of sounding mathematical
formulas in the Ukrainian language gave an opportunity to dub the technical texts of
the Ukrainian language with the help of a language synthesizer, fill the DAISY books
with technical content and convert the mathematical formulas into a text description.
In order to automate the process of creating educational materials in Ukrainian as
a DAISY book, an applied program system for processing Ukrainian-language tech-
nical texts for people with visual impairments has been developed. The basis of the
applied system is the modular structure, which can be implemented as separate func-
tional modules.
Fig. 3. Applied programmed system
The system consists of the following components such as special equipment drivers,
base software and special software. In Fig. 3, in the Special software block, the dot-
ted-out modules that were developed during this study are highlighted, namely:
- module for processing files of various formats (it allows a user of the system
to convert the format of the input book according to their needs);
- keyword search module in the text (it provides search and markup of the text
based on the structural features of the book, as well as mathematical formu-
las, descriptions of drawings, etc.);
- book navigation overlay module (this module is responsible for applying the
selected navigation scheme to the input document and divides it into separate
parts);
- module for converting formulas to a textual description (it ensures the trans-
formation of mathematical formulas and special characters into a text de-
scription in Ukrainian in accordance with the developed rules of conversion);
- content layout and storage module (it is responsible for preserving the struc-
tural parts of the text of the book in separate files, as well as giving an oppor-
tunity to dub them in Ukrainian).
Each module has specific functionality, working with an appropriate set of input
parameters and output data.
The main function of the applied system for processing Ukrainian-language tech-
nical texts is the processing of information, namely collecting (receiving), processing,
storing and displaying. The purpose of the developed system is to maximize the au-
tomation of the process of creating “talking” books, the possibility of working with
Ukrainian-language technical texts, and the availability of this process for a blind
user.
The developed system can be used by a sighted person or a blind user with special
computer skills. An ordinary user usually uses the technical support for the system
such as a monitor, a keyboard, a mouse, speakers or headphones, a microphone, and
external storage media. A blind user uses a keyboard, speakers or headphones, a mi-
crophone, a Braille ruler and a Braille printer, external storage media, and so on.
5 Experimental Determination of the Correctness of the
Developed Software Work
Based on the studied methods of converting formats of mathematical formulas, a
knowledge base is developed that provides a convenient representation of the methods
of transforming one or another format of a mathematical formula into the MathML
language. The knowledge base is a part of the applied program system for processing
Ukrainian technical texts for people with visual impairment.
To test the correctness of the developed software work, five groups of experiments
were carried out to convert the mathematical formulas presented in various formats
into the mathematical markup language MathML, as well as dubbing and perception
of the received MathML formulas (Fig. 4).
For experiments on the convertion of formulas into MathML language, a random
set of mathematical formulas of various complexity is taken.
The test base for the first four groups of experiments contained 100 formulas, with
25 formulas per each group. Among them, 20 formulas are simple arithmetic
expressions, another 20 are trigonometric expressions, 20 ones are integrals and
derivatives, 20 are linear algebra formulas and 20 are series, borders, etc.
During the experiments, free software (UkrVox, Ttm, OpenOffice, etc.) and demo
versions of commercial products (GrindEQ Math Utilities, InftyReader, MathType,
etc.) were used.
Fig. 4. Conducting experimental research
The group of experiments № 1 (*.DOC → «GrindEQ Math» → TeX → Teacode
Latex → MathML).
The first group of experiments was to convert the formula set into the MathML
language written in a Microsoft Word document format and the transformation was
performed step by step:
Step 1: The GrindEQ Math Utilities plugin has converted the formulas written in
the Microsoft Word document into TeX format (Fig. 5). The GrindEQ Math Utilities
plugin contains a set of fully independent components and provides a two-way con-
version between Microsoft Word and LaTeX. There are other methods for presenting
a Microsoft Word document in TeX / LaTeX, such as Word2TeX, MathType,
wvWare, rtf2latex2e, html2latex.
Fig. 5. Converting a mathematical formula into TeX format using GrindEQ Math Utilities
Step 2: At this step, the process of converting the formula from the TeX format to the
MathML language took place. To do this, the Teacode Latex online service was cho-
sen to provide the TeX formulation and convert it to MathML language, and it also
enables to display a formula in a graphic format (* .PNG) stored on a web server [20].
As a result, the text was obtained in the language MathML, which is copied from the
website and stored in a text file with the extension * .MML (Fig. 6).
The group of experiments № 2 (*.PDF → Infty → MathML).
The second group of experiments was to convert the formula set into the MathML
language written in the Adobe Reader, * .PDF format. In the process of these experi-
ments, the transformation was performed step by step:
• Step 1: Microsoft Word text editor (File → Save as → PDF document) is used to
prepare the document with a formula in Adobe Reader format.
Fig. 6. Converting a formula to the MathML language using the online translator Teacode
Latex
• Step 2: It is used the Infty character recognition program to identify and write the
formula in MathML. For this, you need to open the required file with the extension
*.PDF in Infty program, select the recognition language (if you need to recognize the
text further that encounters the formulas), specify in the field “Output File Format”
the output format of the XHTML file (MathML) and begin the process of recognition
using the “Start OCR” button.
As a result of the recognition and manual correction of a formula by the means of
the program Infty (for example, the formula) it is received an XHTML file, in which
this formula is written in the mathematical markup language MathML:
…
b+c
3
=a
…
The group of experiments № 3 (*.HTML → selecting graphic objects → JPG,
PNG, GIF → Infty → MathML).
The third group of experiments was to convert a formula set into a MathML
language written as a * .HTML web page.
Step 1: To select graphic objects in the browser, open a certain web page with the
formula, then save the formula on the computer (clicking the right mouse button on
the formula, choose “Save picture as” and save it to your computer). The result is a
formula in a graphic format (JPG, PNG or GIF).
Step 2: At this step, the formula is recognized in a graphical format saved from a
web page using the Infty tools. To do this, this file is opened in the program Infty - in
the “Input File Format” field the input file format *.PNG is selected, the output
format of the XHTML file (MathML) is specified in the “Output File Format” field.
The formula is recognized by means of the “Start OCR” button. The result of the
recognition is the created XHTML file, which contains the mathematical formula in
the MathML language.
The group of experiments № 4 (MathType → MathML).
The fourth group of experiments was to convert a formula set written with
MathType into the MathML language. Since the default MathType program tools do
not allow you to save formulas in the MathML language, this program is configured
as follows: in the settings of the program, «Cut and Copy Preferences…» submenu,
MathML or TeX is selected - MathML 2.0 (namespace attr) and removed a tick from
"Include MathType data in translation" (Fig. 7). This makes it possible to copy the
formula translated into the MathML language from the MathType environment. The
next step was to save the copied formula in a text editor with * .MML extension.
Fig. 7. Configure MathType to convert the formula to MathML
As to the efficiency of converting a formula into the MathML mathematical markup
language, it should be noted that the most significant errors were encountered during
the recognition of mathematical formulas and their transformation into MathML lan-
guage using Infty. Only 21 formulas were recognized correctly from the 50 formulas
of different complexity (25 formulas from the group of experiments №2 and 25 for-
mulas from the group of experiments №3), which corresponds to 42% accuracy. Due
to the inadequacy of the recognition means of this program, 100% accuracy is not
ensured when recognizing some complex formulas. For example, the formula of me-
dium complexity 3 b + c = a the program Infty recognized wrongly, with such two
errors 3 b + c = . To solve this problem, you need to use an additional tool, it is
an editor of InftyEditor and manually edit the formula. The main disadvantage of this
method of recognition is the large time expenditures for manual editing of irregularly
recognized formulas.
Instead, carrying out the first and fourth groups of experiments gave 100% of the
correct result in the case of converting formulas to the language MathML. This is due
to the accuracy of the programs and the correctness of the used approaches, as well as
the lack of graphical objects that require the use of OCR.
The group of experiments № 5 (dubbing the formulas in Ukrainian transformed
into MathML language).
For this group of experiments, 150 different formulas were taken during the re-
search. All formulas are divided into groups: equations (rational, square, linear),
inequalities, identical expressions, fractional expressions and functions. Each group
includes formulas of various complexity.
Since a person usually takes 7 ± 2 elements (from 5 to 9 objects) at the same time,
which they operate in memory, the formulas have been grouped by complexity. The
complexity of a formula was determined by the number of operands, numbers, and
mathematical operations.
A formula was considered simple if it met at least one of the following
requirements:
• it is less than 5 operands (A, b, x, Z, etc.);
• it is less than 5 mathematical operations (+, =, *, /, etc.);
• it is less than 5 numbers (5, 16, 32, 12.5, etc.).
x ( a + b) 2
For example: a + b = x ; 25 − 15 = 10 ; 16 ; = 4.5 ;
2 c
a+b = 6
The complexity of the formula was considered an average if it met at least one of
the following requirements:
• from 5 to 6 operands;
• from 5 to 6 mathematical operations;
• from 5 to 6 numbers.
(a − b) *5 y − 4a
For example: =x ; x= ; log x y + z = 2ab ;
2+2 2a
de x
= e x ; e x dx = e x
dx
A complicated formula was considered if it satisfied at least one of the following
requirements:
• more than 6 operands;
• more than 6 mathematical operations;
• more than 6 numbers.
1 1
For example: = = + ; (a + b)2 = a2 + 2ab + c2 ;
(−0) 2
+0
P1 = P( A) + P( B) − P( AB) ; S = 2 RH + 2 R2 ; cos a = 1 − sin 2 a
Experiments were consisted of the correct perception by ear of the mathematical
formula dubbing by the developed MathPlay program and recorded it in the notebook
during the listening.
Performing experiments on simple formulas (250 formulas), five respondents
made two errors during playback, making up 0.8% of the total number of records.
According to the calculations of experiments, respondents made 11 mistakes on
formulas of average complexity with the same number of formulas, that is, 4.4% of
the total number of records. The third part of the experiments over complex formulas
showed the following result: 44 errors, or 17.2% of the total number of records.
Consequently, the MathPlay program of dubbing mathematical formulas and
symbols has produced a good result. The program correctly reproduced 693 out of
750 records (92.5%) for formulas of various complexity.
According to the participants of the experiments, the main difficulty during the
experiments was the understanding of the synthesized voice and high speed of
reproduction. In addition, the overall result was influenced by the formula
complexity.
For the most part, the Ukrainian language synthesizer "Ukrainian voice of UkrVox
- Igor" caused errors during the recording of the stated formulas. Consequently, the
development of a high-quality synthesizer of the Ukrainian language will maximize
the sound to the natural voice and accordingly increase the percentage of
comprehension of the dubbing formula for the first time. The problem of developing a
high-quality synthesizer of the Ukrainian language remains relevant and not resolved
until the end for a long time.
6 Conclusion
Further improvement of the developed technologies can make a significant
contribution to solving the problem of people integration with visual impairments into
society, in particular the full education of blind and partially-sighted students in
higher education institutions through inclusion in student groups and school clusters.
As a result of the study of the problem of automatic voice recognition of
mathematical formulas and symbols, experiments have been carried out which
showed that using the MathML tag conversion rule-making system, a qualitative
program of voice-assertion of formulas in the Ukrainian language (92.5%) was
developed for various complexity formulas.
The obtained results already allow application of the applied program system for
the processing Ukrainian-language technical texts in practice for the training of blind
users. A knowledge base has been formed with a description of the rules for
translating mathematical formulas from a plurality of formats into the mathematical
markup language MathML, from which a text file with a description for the
synthesizer of the Ukrainian language is generated. As a result, it was possible to
develop Ukrainian-language textbooks on technical disciplines in accordance with the
DAISY standard. Such books can be used, first of all, to train people with disabilities
in mathematical and applied disciplines in both secondary and higher educational
establishments.
To further improvement of the means of sounding mathematical formulas in
Ukrainian, it should be developed a high-quality synthesizer of the Ukrainian
language and improved the methods of data preparation. Hence, it is planned to
improve the rules of the formula statement with the addition of terms and clarify the
rules of pronouncing large formulas, as well as automate the process of overlaying
navigation on the DAISY book pages.
Computer-technological and methodological analogues of developments in
Ukraine are not yet available. With regard to the results of foreign research and
development, the presentations are technologically proportional to the world-wide
achievements in the field of advanced information technology focused on people with
special needs.
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