Sociofeedback by application

• Main Author: Yan, Aiden Guo Ting
• Other Authors: Justin Dauwels
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/71975
• Institution: Nanyang Technological University

This project focuses on the development of an application with real-time feedback for improving speaking dialog as its functionality. The deployment platform of the application is in Android environment, which is a widely supported and open source environment. It was also optimized to accomplish real-time speech signal processing and features classification standalone on the Android mobile device. This paper illustrates the process of enhancement of previously developed Sociofeedback Application on Google Glass by a Final Year Student. The application will set to be used in dialogs, lecture, presentation or speech etc. It will able to analyse the user voice input and provides analysed low-level features as feedback in a summary report. In future, the application has the potential to process more accurate and complex signal processing algorithm on the mobile device itself, which these processing algorithm was conventionally done on computer machine using on MatLab, C++ and etc. that has no portability in mind. With an application, it will be easily deployable through mobile application store and directly implemented by any users for environments such as teaching, debating, presentation, speech training, etc.