Download - Device for Text to Speech Production and to Braille Script

Proceedings of the International Conference on Emerging Trends in Engineering and Management (ICETEM14)

30 31, December 2014, Ernakulam, India

174

DEVICE FOR TEXT TO SPEECH PRODUCTION AND TO

BRAILLE SCRIPT

Hima Pradeep V, Jeevan K M, Miji Jacob

Department of Electronics and Communication Engineering, Sree Narayana Gurukulam College of Engineering,

Kadayiruppu, Kolencherry, India

ABSTRACT

Writing is a very effective means of communicating our thoughts to people. We use scripts provided by the

language to convey our thoughts to paper. However, in case of people who dont have the sense of vision, they use a

different type of script, known as Braille, named after its founder, Louis Braille. It is unlike the scripts that sighted use

for writing. The current methods by which the unsighted and deaf are able to communicate are few, and all have serious

drawbacks. These people completely depend on Braille and Audio recordings provided. Audio recordings provided are

limited. Here we attempt to devise a system that will take the image of the text and convert it into speech& propose a

system which will take image of the text and convert it to Braille script. We hope that this system will be helpful in

bridging this communication gap that exists between sighted & non-sighted people. In this system MATLAB is used to

process the image & speech signals.

Keywords: Braille Script, Deaf Person, Image Acquisition, Threshold Value, Text-to-Speech.

1. INTRODUCTION

The learning process for the unsighted and deaf person is a difficult task. The current methods by which the

unsighted and deaf are able to communicate are few, & all have serious drawbacks. Braille writing is a widely spread

means of communication for blind or partially sighted people. It consists of a system of six or eight possible dot

combinations that are arranged in a fixed matrix, called a cell. Every dot can be set or cleared, giving 61 combinations in

six-dot & 256 combinations in eight-dot Braille. All dots of a Braille page should fall on the intersections of an

orthogonal grid. When texts are printed double-side (recto-verso), the grid of the verso text is shifted so that its dots fall

in between the recto dots. Braille has a low information density. An average page of 25x 29cm, can have 32 characters

on a line & 27 lines in a page. A typical dot has a diameter of 1.8 mm.

This paper presents a solution to such a problem, makes learning process for an unsighted & deaf person more

easier. As all textbooks will not be available in Braille script as well as Audio recordings of all textbooks are not

available. We will take the image of content in the textbook and it will be reproduced as sound for persons who are only

blind and as Braille script for persons who are both blind & deaf.

The remainder of this paper is organized as: Section 2 describes the block diagram for proposed solution and

section 3 describes software implementation and results. Section 4 concludes the paper.

INTERNATIONAL JOURNAL OF ELECTRONICS AND

COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)

ISSN 0976 6464(Print)

ISSN 0976 6472(Online)

Volume 5, Issue 12, December (2014), pp. 174-179

IAEME: http://www.iaeme.com/IJECET.asp

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2. DESCRIPTION OF THE PROPOSED SYSTEM

Fig.1 shows the basic block diagram of device to convert text to speech. The image of text is captured by

camera using image acquisition. The contrast adjustment is done using image enhancement technique. Filtering is done

for noise reduction. The edges in the image is determined with the help of edge detection methods, hence finding the

boundaries. Cropping is done here. The text present in the image are segmented into separate letters & extracted letters

is compared with the letters early stored in the system for character recognition. We use correlation matching technique

for the purpose. The corresponding letter is played. Here the letters obtained are separated to a words. We set a threshold

value for space, if value obtained is greater than threshold value it is considered as letter else space &thus separation of

words take place. Text-to-speech (TTS) synthesizer would start with the words in the text, convert each word one-by-one

into speech, & concatenate the result together. Thus the voice is produced from a text.

S SPEAKER

Figure 1: Block diagram for text to speech production

Fig.2 shows the proposed block diagram of device to convert text to Braille script. The image of text is captured

by camera using image acquisition. The contrast adjustment is done using image enhancement technique. Filtering is

done for noise reduction. The edges in the image is determined with the help of edge detection methods, hence finding

the boundaries. Cropping is done here. The text present in the image are segmented into separate letters & extracted

letters is compared with the letters early stored in the system for character recognition. We use correlation matching

technique for the purpose. The corresponding letter is played. Here the letters obtained are separated to a words. We set a

threshold value for space, if value obtained is greater than threshold value it is considered as letter else space &thus

separation of words take place. Characters are sent to the

Graphical User Interface (GUI) on the PC. The American Standard Code for Information Interchange (ASCII)

value of the character to be read can be sent wirelessly from PC to Microcontroller using the wireless CC 2500 Radio

Frequency (RF) Transreceiver module. The American Standard Code for Information Interchange (ASCII) value of the

character sent from the PC can be converted to the corresponding Braille code using a conversion algorithm. This

conversion program can be written in an Embedded C language and it can be recorded in microcontroller. The output of

the microcontroller can be taken from the general purpose input/output pins of the development board in the form of

voltages that is either 0 Volts or 5 Volts.

A six bit number in binary/hexadecimal form can be obtained from the output of the microcontroller

corresponding to the Braille code of the character. The output from the six Input/output pins can be further given to the

tactile display made of six solenoids that represent the Braille characters, the device will be having only a single Braille

cell. The touchpad can be interfaced to the device so that the user can navigate through the textbooks using gestures like

forward stroke, backward stroke, up or down movements.

CAMERA IMAGE

ACQUISITION

IMAGE

ENHANCEMENT

FILTERING

EDGE

DETECTION

CHARACTER

SEGMENTATION

CHARACTER

RECOGNITION

SEPARATION

OF WORDS

TEXT TO

SPEECH

CONVERSION



176

S

Figure 2: Block diagram for text to braille script

2.1. Camera

The camera here we use is a normal webcam which is of low cost. The advantage of using a webcam is that it

can be interfaces very easily and is able to take pictures real time. However it is preferred to use camera of better

resolution for better results.

2.2. Image acquisition

Matlab has image acquisition toolbox for getting image signals from a video device. For image capture, the

device configured must have a supporting adaptor & should be compatible with system resolution and colour patterns. A

video object is initialized here & the images are captured at desired intervals after setting required parameters.

2.3. Image Enhancement

This is improvement of digital image quality. Contrast adjustment is made by histrogram acquisition. Histeq is

the command used to do histrogram acquisition. Grayscale image only works.

2.4. Filtering The technique of median filtering is used. A median filter operates over window by selecting the median

intensity in the window. Median filter is an example of Non-linear filtering, often used to remove noise. Median filtering

is very widely used in digital image processing because under certain conditions, it preserves edges while removing

noise.

2.5. Edge Detection This is the image processing step in Matlab. At first the edges in the image is determined with the help of edge

detection methods, hence finding the boundaries. Cropping is done here. Performs a contrast enhancement if needed. The

image is then resized.

CAMERA IMAGE

ACQUISITION

IMAGE

ENHANCEMENT

FILTERING

EDGE

DETECTION

CHARACTER

SEGMENTATION

CHARACTER

RECOGNITION

GUI ON

PC

CC 2500

TRANSRECEIVER

MODULE

ASCII TO

BRAILLE

CONVERSION

ALGORITHM

MICROCONTROLLER SOLENOIDS

TOUCHPAD

SEPARATION

OF

WORDS



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2.6. Character Segmentation Partition of image into several components. Segmentation is an important part of practically any automated

image recognition system, because it is at this moment that one extracts the interesting objects, for further processing

such as description or recognition. Segmentation of an image is in practice the classification of each image pixel to one

of image parts.

2.7. Character Recognition The captured feature extracted image is compared with the images early stored in the system for character

recognition. We use correlation matching technique for the purpose. The corresponding letter is played.

2.8. Separation of words

Here the letters obtained are separated to a words. We set a threshold value for space, if value obtained is greater

than threshold value it is considered as letter else space and thus separation of words takes place.

2.9. Text to Speech Conversion

Text-to-speech (TTS) synthesizer would start with the words in the text , convert each word one-by-one into

speech and concatenate the result together. The task of a TTS System is thus a complex one that involves mimicking

what human readers do. Windows Speech Application Program Interface is used here.

3. SOFTWARE IMPLEMENTATION

The whole system is implemented in Matlab environment. Image quality should be considerably well to obtain

efficient output. Text-to-speech synthesizer (TTS) would start with the words in the text, convert each word one-by-one

into speech and concatenate the result together. The task of a TTS system is thus a complex one that involves mimicking

what human readers do. Windows Speech Application Program Interface is used here. The Speech Application

Programming Interface or SAPI is an API developed by Microsoft to allow the use of speech recognition and speech

synthesis within Windows applications. It is possible for a 3rd

-party company to produce their own Speech Recognition

& Text-To-Speech engines or adapt existing engines to work with SAPI. Here we use default sampling frequency 16000.

Speed can be set between -10 to +10. Normal speed is zero. Thus the text can be converted to speech. The proposed

system of converting text to Braille script can be doned by using GUI.

3.1. Simulation Windows

Figure 3: window for to select the mode



178

Figure 4: window to get preview of image

Figure 5: window to capture image

Figure 6: window to process image

Here image captured will be processed. The text is converted to speech by TTS synthesizer.



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4. CONCLUSION

The device is a considerable improvement over currently available text to speech device. In particular, the

device is easy to use with little or no training used in most situations. The speed of hearing can be set & allow all people

to hear sound clearly. The trainers can easily train blind & deaf people. Thus blind & deaf people can perform their

studies easily. The implementation of text to Braille script can be done using solenoids. With slight modification the

system can be used for dumb people to communicate over telephone.

5. REFERENCES

[1] G.J. Awcock and R Thomas, Applied Image Processing, MacMillan Press Limited, 1995. [2] Agui T. And Nagao T. Computer Image Processing and Recognition, Tokyo: Shoho-do, 1994. [3] Gonzalez R.C. and Woods R. E., Digital Image Processing, Addison-Wesley, 1992. [4] Marr D. And Hildreth, Theory of edge detection, Proc. of Royal Society London, B207, 1980, pp. 198-217. [5] S. Thomas, M. Nageshwar Rao, H. A. Murthy, & C. S. Ramalingam, Natural sounding speech based on

syallable-like units, in EUSIPCO, Florence, Italy, 2006.

[6] P. V. S. Rao and R. B. Thosar, A Programmimg system for studies in speech synthesis, IEEE Trans.Acoust., Speech and Signal Processing , vol. 22 , no. 3, pp. 217-225, 1974.

[7] Sproat, R. And Olive, J. Text-to-Speech Synthesis Digital Signal Processing Handbook, Crc Press LLC, 1999. [8] Mukul Bandodkar, Virat Chourasia, Low Cost Real-Time Communication Braille. [9] Hand-Glove for Visually Impaired Using Slot Sensors and Vibration Motors, International Journal of

Electrical, Robotics, Electronics and Communications Engineering Vol:8, No:6, 2014.

[10] Vineeth Kartha, Dheeraj S. Nair, Sreekant S., Pranoy P. and Dr. P. Jayaprakash, DRISHTIA Gesture Controlled Text to Braille Converter, IEEE, 2012.

[11] A. A. Supekar, Prof. S. B. Somani and Prof. V.V. Shete, A Teaching System for Non-Disabled People Who Communicate with Deaf blind People, International Journal of Electronics and Communication Engineering &

Technology (IJECET), Volume 4, Issue 4, 2013, pp. 221 - 225, ISSN Print: 0976- 6464, ISSN Online:

0976 6472.

Download - Device for Text to Speech Production and to Braille Script

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