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Current Trends in Science and Technology

an Open Access Publication ISSN: 0976-9730 | 0976-9498

Computer Science

JEvi and JVoicepad Voice Recognition Software

Miss.Shweta Pratap Karkhile, Prof.Pawar P.U
1Adsul Technical Campus Collage of Engginering, Ahmednagar, Department of Computer Engineering Chas, Ahmednagar, India 2Assistant Professor ATCOE chas Department of Computer Engineering, Chas, Ahmednagar, India
Online First: February 13, 2018
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Abstract

There are 45 million blind people and 135 million visually impaired people worldwide. Disability of visual text reading has a huge impact on the quality of life for visually disabled people. Although there have been several devices designed for helping visually disabled to see objects using an alternating sense such as sound and touch, the development of text reading device is still at an early stage. Existing systems for text recognition are typically limited either by explicitly relying on specific shapes or colour masks or by requiring user assistance or may be of high cost. Therefore we need a low cost system that will be able to automatically locate and read the text aloud to visually impaired persons. The main idea of this project is to recognize the text character and convert it into speech signal. The text contained in the page is first pre-processed. pre-processing module prepares the text for recognition. Then the text is segmented to separate the character from each other. Segmentation is followed by extraction of letters and resizing them and stores them in the text file. This text is then converted into speech.

Keyword : MFCC, acoustic model,hidden markov model,TTS

  Submitted
Feb 12, 2018
Published
Feb 13, 2018
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References

1. Ani R,Effy Maria,”Voice Assisted Text Reading system for Visually Impaired persons Using TTS Method”Department of Electronics and Communication Engineering,Dr.N.G.P Institute of Technology. 2. Rajesh Kumar Aggarwal,Mayank Dave(2011).Acoustic modeling problem for automatic speech recognition system part I. 3. M.A.Anusuya and S.K.Katti, “Speech Recognition by Machine:A Review”,:A Review",(IJCSIS)International Journal of Computer Science and Information Security,vol..6,no.3,pp. 181-205,2009. 4. Irakli Kardava,Jemal Antidze Sokhumi,”Solving the problem of the Accents for Speech Recognition Systems”,June2016. 5. Wiqas Ghai and Navdeep Singh,”Review on Automatic speech Recognition ”,May2012. 6. Hasan Gyulyustan,Svetoslav Enkov “Experimental Speech recognition system based on Raspberry pi 3,”May 16-17. 7. Jacob Benesty,M.Mohan Sondhi “Handbook of speech processing”,springer,2008. 8. [AlexandreTrilla and Francesc Alías. (2013), “Sentence- Based Sentiment Analysis for Expressive Text-to-Speech”, IEEE Transactions onAudio, Speech, and Language Processing, Vol. 21, Issue. 2. pp. 223-233. 9. Balakrishnan G. Sainarayanan G. Nagarajan R. and Yaacob S. (2007) „Wearable real-time stereo vision for the visually impaired‟, Vol. 14, No. 2, pp. 6–14. 10. Chucai Yi. YingLiTian.AriesArditi. (2014), „Portable Camera-based Assistive Text and Product Label Reading from handheld Objects for Blind Persons‟, IEEE/ASMETransaction onMechatronics vol.3,Issue.1 11. Deepa Jose V. and Sharan R. (2014), „A Novel Model for Speech to Text Conversion‟, International Refereed Journal of Engineering and Science (IRJES) Vol.3, Issue.1, pp. 39-41. 12. Goldreich D. and Kanics I. M. ( 2003), „Tactile Acuity is Enhanced in Blindness‟, International Journal of Research And Science, Vol. 23, No. 8,pp. 3439–3445. 13. Joao Guerreiro and Daniel Gonçalves (2014), „Text-to- Speech: Evaluating the Perception of Concurrent Speech by Blind People‟, International journal of computer technology, Vol. 6, No. 8, pp. 1-8. 14. Manduchi R. and Miesenberger K. (2012), „Mobile Experimental Study‟, Springer-In Computers Helping People with Special Needs, Vol. 2, No.7383, pp. 9–16.
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References

1. Ani R,Effy Maria,”Voice Assisted Text Reading system for Visually Impaired persons Using TTS Method”Department of Electronics and Communication Engineering,Dr.N.G.P Institute of Technology.
2. Rajesh Kumar Aggarwal,Mayank Dave(2011).Acoustic modeling problem for automatic speech recognition system part I.
3. M.A.Anusuya and S.K.Katti, “Speech Recognition by Machine:A Review”,:A Review",(IJCSIS)International Journal of Computer Science and Information Security,vol..6,no.3,pp. 181-205,2009.
4. Irakli Kardava,Jemal Antidze Sokhumi,”Solving the problem of the Accents for Speech Recognition Systems”,June2016.
5. Wiqas Ghai and Navdeep Singh,”Review on Automatic speech Recognition ”,May2012.
6. Hasan Gyulyustan,Svetoslav Enkov “Experimental Speech recognition system based on Raspberry pi 3,”May 16-17.
7. Jacob Benesty,M.Mohan Sondhi “Handbook of speech processing”,springer,2008.
8. [AlexandreTrilla and Francesc Alías. (2013), “Sentence- Based Sentiment Analysis for Expressive Text-to-Speech”, IEEE Transactions onAudio, Speech, and Language Processing, Vol. 21, Issue. 2. pp. 223-233.
9. Balakrishnan G. Sainarayanan G. Nagarajan R. and Yaacob S. (2007) „Wearable real-time stereo vision for the visually impaired‟, Vol. 14, No. 2, pp. 6–14.
10. Chucai Yi. YingLiTian.AriesArditi. (2014), „Portable Camera-based Assistive Text and Product Label Reading from handheld Objects for Blind Persons‟, IEEE/ASMETransaction onMechatronics vol.3,Issue.1
11. Deepa Jose V. and Sharan R. (2014), „A Novel Model for Speech to Text Conversion‟, International Refereed Journal of Engineering and Science (IRJES) Vol.3, Issue.1, pp. 39-41.
12. Goldreich D. and Kanics I. M. ( 2003), „Tactile Acuity is Enhanced in Blindness‟, International Journal of Research And Science, Vol. 23, No. 8,pp. 3439–3445.
13. Joao Guerreiro and Daniel Gonçalves (2014), „Text-to- Speech: Evaluating the Perception of Concurrent Speech by Blind People‟, International journal of computer technology, Vol. 6, No. 8, pp. 1-8.
14. Manduchi R. and Miesenberger K. (2012), „Mobile Experimental Study‟, Springer-In Computers Helping People with Special Needs, Vol. 2, No.7383, pp. 9–16.
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