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Speech Synthesis System for Detected Objects by Smart Phone
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 Title & Authors
Speech Synthesis System for Detected Objects by Smart Phone
Kwon, Soon-Kak;
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This paper designs an application for detecting various objects using a smart phone with camera sensor, then implements the application that detects the number of faces in front of a user by using the Face API provided by android and generates a speech to the user. For implementing the application, the GoF strategy pattern is applied to design the application. It provides some advantages; first, the algorithm development schedule can separate the whole application development schedule; next, it makes easier to add the algorithm. For example, another detecting algorithm for the other objects (character, motion detection) that may be developed in the future, or it may be replaced by a more high-performance algorithm. With the propose method, a general smart phone can make some advantages that can provide information of various objects (such as moving people and objects, and detected character from signboards) to the person who is visually impaired.
Camera;TTS;Face Detection;Strategy Pattern;
 Cited by
스마트폰 자이로센서를 이용한 시각장애인용 광학문자인식 방법,권순각;김흥준;

한국산업정보학회논문지, 2016. vol.21. 4, pp.13-20 crossref(new window)
An Optical Character Recognition Method using a Smartphone Gyro Sensor for Visually Impaired Persons, Journal of the Korea Industrial Information Systems Research, 2016, 21, 4, 13  crossref(new windwow)
J. Yang, A Study on Syllable-level Concatenation for HMM-based Mixed-lingual Text-to-speech, Master's Thesis of Gwangju Institute of Science and Technology, 2010.

Demo Software: SIFT Keypoint Detector, (accessed Jan., 05, 2016).

Character recognition,, (accessed Jan., 13, 2016).

character recognition,, (accessed Jan., 13, 2016).

N. Kim, D. Kim, S. Kim, and S. Kwon, “Vocabulary Generation Method by Optical Character Recognition,” Journal of Korea Multimedia Society, Vol. 18, No. 8, pp. 943-949, 2015. crossref(new window)

E. Go, Y. Ha, S. Choi, K. Lee, and Y. Park, “An Implementation of an Android Mobile System for Extracting and Retrieving Texts from Images,” Journal of Digital Contents Society, Vol. 12, No. 1, pp. 57-67, 2011. crossref(new window)

M. Kim, “Individual Identification Using Ear Region Based on SIFT,” Journal of Korea Multimedia Society, Vol. 18, No. 1, pp. 1-8, 2015. crossref(new window)

G. Yoo, K. Jeong, and H. Moon, "Object Recognition Based on Speed Up Robust Feature Algorithm(SURF) for Smartphone Environment," Proceeding of The Institute of Electronics Engineers of Korea, pp. 544-545, 2010.

The development of face recognition technology and content services,, (accessed Apr., 10, 2014).

D. Kim, M. Sohn, and S. Lee, "A Study on Face Recognition Method Based on Binary Pattern Image under Varying Lighting Condition," Proceeding of The Institute of Electronics Engineers of Korea, pp. 61-74, 2012.

J. Kim, “Face Recognition by Fiducial Points Based Gabor and LBP Features,” The Journal of the Korea Contents Association, Vol. 13, No. 1, pp. 1-8, 2013. crossref(new window)

M. Abdur Rahim, M. Najmul Hossain, T. Wahid, and M. Shafiul Azam, “Face Recognition using Local Binary Patterns (LBP),” Global Journal of Computer Science and Technology, Vol. 13, No. 4, pp. 1-8, 2013.

Object Recognition,, (accessed Jan., 11, 2016).

The 7 Best Android Text-To-Speech Engines,, (accessed Jan., 05, 2016).

The Implementation of ths TTS in the Android,, (accessed Jan., 05, 2016).

Android Developer Text To Speech,, (accessed Jan., 05, 2016).

Using the Google TTS(TextToSpeech),, (accessed Jan., 05, 2016).

E. Gamma, R. Johnson, R. Johnson, and H. Vissides, Design Patterns, Elements of Reusable Object-Oriented Software, Addison-Wesley Publishing Company, Boston, 1995.