Abstract—This paper invested an intelligent medication reminding system that composed of optical character recognition (OCR) and text to speech (TTS) for visually challenged individuals. This approach has been implemented as an ARM-based embedded system that is adopted here to provide the service to extract the text from document and synthesize speech to generate the speech sound for the visually impaired individuals. As a domain specific reading machine, the proposed intelligent medication reminding system uses the convolutional neural network (CNN) as the optical character recognition (OCR) core engine to recognize the Chinese character, the HMM/DNN-based speech synthesis system is adopted as the pronunciation mechanism to achieve the functionality of text to speech (TTS). Since the recognition error resulted from optical character recognition, the spelling checking module based on n-gram models are also completed by detecting and correcting the error characters. For evaluating the proposed approach, several experiments are designed for the users. According to the experimental results, we can find the proposed approach can obtain the improvement in daily usage. That is to say, the developed embedded system is practical and effective.
Index Terms—Convolutional neural network, HMM/DNN-based speech synthesis system, embedded system, optical character recognition, reading machine, spell check, text to speech.
The authors are with the National Chiayi University, Chia-Yi City, Taiwan (e-mail: firstname.lastname@example.org).
Cite: Jui-Feng Yeh, Chan-Yi Liu, Sheng Chen, Jia-Yu Lin, and Li-Ting Zhang, "Intelligent Medication Reminding System for Visually Challenged Groups," International Journal of Machine Learning and Computing vol. 10, no. 5, pp. 685-691, 2020.Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).