A Voice Based Assistant Using Google Dialogflow and Machine Learning

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Dr. Jaydeep Patil, Ekta Bhushan, Rucha Khartadkar, Atharva Shewale, Alister Fernandes


Virtual Personal Assistant (VPA) is one of the most successful results of Artificial Intelligence, which has given a new way for the human to have its work done from a machine, just like a normal person. This paper provides methodologies and concepts used in making of a Virtual Personal Assistant (VPA) and thereby going on to use it in different software applications. In this project, we are trying to make a Virtual Personal Assistant ERAA which will include the important features that could help in assisting ones’ needs. Keeping in mind the user experience, we will make it as appealing as possible, just like other VPAs. Various Natural Language Understanding Platforms like IBM Watson and Google Dialogflow were studied for the same. In our project, we have used Google Dialogflow as the NLU Platform for the implementation of the software application. The User-Interface for the application is designed with the help of Flutter software platform. All the models used for this VPA will be designed in a way to work as efficiently as possible. Some of the common features which are available in most of the VPAs will be added. We will be implementing ERAA via a smartphone application, and for future scope, our aim will be to implement it on the desktop environment. The following Paper ensures to provide the methodologies used for development of the application. It provides the obtained outcomes of the features developed within the application. It shows how the available natural language understanding platforms can reduce the burden of the user, and therefore going on to develop a robust software application.


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