Total views : 193

Text to Speech Conversion

Affiliations

  • Department of CSE, K L University, Vaddeswarm, Guntur – 522502, Andhra Pradesh, India
  • Department of ECM, K L University, Vaddeswarm, Guntur – 522502, Andhra Pradesh, India

Abstract


The present paper has introduced an innovative, efficient and real-time cost beneficial technique that enables user to hear the contents of text images instead of reading through them. It combines the concept of Optical Character Recognition (OCR) and Text to Speech Synthesizer (TTS) in Raspberry pi. This kind of system helps visually impaired people to interact with computers effectively through vocal interface. Text Extraction from color images is a challenging task in computer vision. Text-to-Speech conversion is a method that scans and reads English alphabets and numbers that are in the image using OCR technique and changing it to voices. This paper describes the design, implementation and experimental results of the device. This device consists of two modules, image processing module and voice processing module. The device was developed based on Raspberry Pi v2 with 900 MHz processor speed.

Keywords

Image Processing, OCR, Text Extraction, Text-to-speech, Voice Processing.

Full Text:

 |  (PDF views: 730)

References


  • Archana A, Shinde D. Text pre-processing and text segmentation for OCR. International Journal of Computer Science Engineering and Technology. 2012:810–12.
  • Mithe R, Indalkar S, Divekar N. Optical character recognition. International Journal of Recent Technology and Engineering. 2013 Mar; 2(1).
  • Smith R. An overview of the Tesseract OCR engine, USA: Google Inc; 2007.
  • Shah H, Shah A. Optical character recognition of Gujarati numerical. International Conference on Signals, Systems and Automation. 2009; 49–53.
  • Monk S. Raspberry pi cook.
  • Text localization and extraction in images using mathematical morphology and OCR Techniques; 2013.
  • Vanitha E, Kasarla PK, Kuamarswamy E. Implementation of text- to-speech for real time embedded system using Raspberry Pi processor. International Journal and Magazine of Engineering Technology Management and Research. 2015 Jul:1995.
  • Kumar GS, Krishna MNVLM. Low cost speech recognition system running on Raspberry Pi to support Automation applications. International Journal of Engineering Trends and Technology. 2015; 21(5).
  • Bhargava A, Nath KV, Sachdeva P, Samel M. Reading assistant for visually Impaired. International Journal of current Engineering and Technology. 2015 Apr; 5(2).
  • Gomes LCT, Nagle EJ, Chiquito JG. Text-to-speech conversion system for Brazilian Portuguese using a formant-based synthesis technique. LPS-DECOM-FEEC-Unicamp.
  • Sim Liew Fong, Abdelrahman Osman Elfaki, Md Gapar bin Md Johar & Kevin Loo Tow Aik, Mobile Language Translator, 5th Malaysian Conference in Software Engineering (Misses); 2011.
  • Kamesh DBK, Nazma SK, Sastry JKR, Venkateswarlu S. Camera based text to speech conversion, obstacle and currency detection for blind persons. Indian Journal of Science and Technology. 2016 Aug; 9(30).

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.