Translating System with Android and Raspberry PI
Jae Moon Lee1, In-Hwan Jung2, Kitae Hwang3
1Jae Moon Lee, Department of School of Computer Engineering, Hansung University, Samseongyoro-Gil, Seongbuk-Gu, Seoul, (Korea), East Asian.
2In-Hwan Jung, Department of School of Computer Engineering, Hansung University, Samseongyoro-Gil, Seongbuk-Gu, Seoul, (Korea), East Asian.
3Kitae Hwang, Department of School of Computer Engineering, Hansung University, Samseongyoro-Gil, Seongbuk-Gu, Seoul, (Korea), East Asian.
Manuscript received on 20 June 2019 | Revised Manuscript received on 27 June 2019 | Manuscript Published on 22 June 2019 | PP: 220-224 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H10400688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recently, translation systems have been focused due to growth of web services and smart phones. This paper aims to develop noble translation system with smart phone to IoT device. Methods/Statistical analysis: The proposed system uses a smart phone and an IoT device for translation. The IoT device works simply to transmit recorded audio to smart phones and to receive and display the translated context. The smart phone requests to translation through web services. The smart phone also transmits result to an IoT device or displays it. An advantage of such methods is that it requires minimum function from the IoT. Findings: An Android smart phone was used to develop this system. Raspberry pi was used as the relevant IoT device. Both devices recorded audio with the same method. Recording was conducting through a PCM method. Sampling Rates were selected as variable, so that the size of the recording file could be selected as needed. Raspberry pi delivers the recorded audio to the Android smart phone via bluetooth. And it receives the translated text, and displays it. The smart phone converts the recorded/received audio file to text, and translates it into a desired language. Google Speech Service was used to convert the audio file to text. The Naver Clova was used to translate the text. Both web services have applied Artificial Intelligence technology, and thus yielded results of satisfactory quality. Improvements/Applications: The greatest advantage of the proposed system is the minimized function of the IoT device. Thus, it is possible to develop the translating system with minimum cost.
Keywords: Smart Phone, IoT, Web Services, Speech to Text, Translation.
Scope of the Article: Smart Learning Methods and Environments