Optical Character Reader & Text To Speech Conversion using Correlations & Speech Synthesis
Avinash Rai1, Shivani Sonker2
1Dr. Avinash Rai*, Department of Electronics and Communication, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, (M.P), India.
2Ms. Shivani Sonker, Department of Electronics and Communication, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, (M.P), India.
Manuscript received on July 22, 2020. | Revised Manuscript received on August 03, 2020. | Manuscript published on August 10, 2020. | PP: 478-483 | Volume-9 Issue-10, August 2020 | Retrieval Number: 100.1/ijitee.J76190891020 | DOI: 10.35940/ijitee.J7619.0891020
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Abstract: In the modern era of image processing, recognizing content or information from an image is process of electronic conversion into machine encoded text. Advanced systems that are capable of producing high accuracy for multi-font recognition are now becoming commonplace, and with the support of digital consent formatting. Some programs are able to retrieve formats that are very close to the original page including images, columns, and other non-text items. Proposed system is able to recognize text from an image and convert it into editable text along with speech conversion. System uses Correlation model for OCR (Optical Character Recognition) and Speech Synthesis for TTS (Text To Speech) conversion. Correlation is a measurement of the similarities between two similar objects such as the predefined alphabets and recognizing a combination of those alphabets from an image. Speech synthesis is an artificial expression of human speech. The computer program that has been used this feature is called a speech computer as well as speech synthesizer that can be implemented on the basis of software or hardware primitives. The text-to-speech system (TTS) converts a standard language text into a speech; some programs provide figurative language presentations such as typed text in speech. System is capable enough to acquire high level of accuracy with less false recognition. It is required to built an effective text scanner that can recognize text from an image with less error rate. System has been implemented in MATLAB and various pre-processing filters have been applied for better enhancement and extraction. Hand written text can also be recognized with an effective manner.
Keywords: OCR, TTS, Speech Synthesis, Correlation Model, Machine Encoding, Image Processing.
Scope of the Article: Machine Learning