International Journal of Computer Techniques Volume 12 Issue 4 | AI VOICE ASSISTANT ANDROID APP USING KEYWORD MATCHING AND NLP
AI Voice Assistant Android App Using Keyword Matching and NLP
Authors:
Ms. Kuramana Yasodha, MCA Student
Mr. M. Bala Naga Bhushanamu, Assistant Professor
Department of Computer Science, Andhra University College of Engineering, Visakhapatnam, India
Email: kuramanayasodha9581977919@gmail.com, balu91@gmail.com
Journal: International Journal of Computer Techniques – Volume 12 Issue 4
Publication Date: July – August 2025
ISSN: 2394-2231
URL: https://ijctjournal.org/
Abstract
This paper presents an offline-first AI voice assistant Android app built using Java and Android Studio. It uses rule-based keyword matching and lightweight NLP techniques such as tokenization, normalization, and pattern matching. The assistant performs core smartphone tasks—calling, messaging, alarms, and app launching—without internet connectivity. It leverages Android’s SpeechRecognizer and TextToSpeech APIs, supports optional online queries, and is optimized for low-resource environments, enhancing privacy and accessibility.
Keywords
Artificial Intelligence, Text-To-Speech, Speech Recognition, Java, XML, Android Studio, Natural Language Processing, Tokenization, Normalization, Pattern Matching, Keyword Matching, Rule-Based Decision Making
Conclusion
The proposed AI voice assistant app offers a secure, lightweight, and offline-capable voice interface for Android devices. It uses rule-based NLP and keyword matching to execute commands efficiently. Designed for low-connectivity regions and privacy-conscious users, the app demonstrates fast response times and compatibility with low-end devices. Future enhancements may include deep learning integration and expanded command sets.
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