| Issue |
ITM Web Conf.
Volume 27, 2019
The 9th International Conference on Digital Information and Communication Technology and its Applications (DICTAP2019)
|
|
|---|---|---|
| Article Number | 05001 | |
| Number of page(s) | 4 | |
| Section | Signal Processing, Pattern Recognition and Applications | |
| DOI | https://doi.org/10.1051/itmconf/20192705001 | |
| Published online | 10 May 2019 | |
Speech Recognition and Speech Synthesis Models for Micro Devices
Information Systems Department, Faculty of Science and Engineering, Soka University, Japan
* Corresponding author: e18d5201@soka-u.jp
With the advent and breakthrough of interaction between humans and electronic devices using speech in communication, we have seen a lot of applications using speech recognition and speech synthesis technology. There are some limitations we have identified to these applications. Availability of a lot of resources and internet connectivity have made it possible in making case but with limited resources it is quite difficult to achieve this feat. As a result, it limits the application of the technology into micro devices and deploying them into areas where there are no internet connectivity. In this article, we developed a smaller Deep Neural Network models for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) for communication on micro devices such as Raspberry Pi. We tested and evaluated the models of the system. The accuracy and the performance of the models to be implemented on micro devices shows that they are good for application development in micro devices.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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