ANKIT PROJECT-merged.pdf

A Minor Project Report on Voice Assistant for Personalized Task Management Submitted by Ankit Verma (0112CA23102...

A Minor Project Report on Voice Assistant for Personalized Task Management Submitted by Ankit Verma (0112CA231020) Submitted in partial fulfillment of the requirement for the degree of “Master of Computer Application” Bansal Institute of Science and Technology, Bhopal Affiliated to Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal July-Dec 2024 Guided by Submitted By: Prof. Anshi Shrivastava Ankit Verma Asst. Prof., MCA (BIST) E. No. – 0112CA231020  Bansal Institute of Science and Technology, Bhopal Master of Computer Application DECLARATION I Ankit Verma, 0112CA231020 student of Master of Computer Applications, Bansal Institute of Science and Technology, Bhopal, hereby declare that the work presented in this Minor Project is outcome of my own work, is bonafide and correct to the best of my knowledge and this work has been carried out taking care of Engineering Ethics. The work presented does not infringe any patented work and has not been submitted to any University for the award of any degree or any professional diploma. Ankit Verma (0112CA231020)  BANSAL INSTITUTE OF SCIENCE AND TECHNOLOGY, BHOPAL MASTER OF COMPUTER APPLICATION CERTIFICATE This is to certify that the work embodied in this dissertation entitled “Voice Assistant for Personalized Task Management” has been satisfactorily completed by Ankit Verma (0112CA231020). It is a bonafide piece of work, carried out under my guidance in the Master of Computer Applications, Bansal Institute of Science and Technology, Bhopal for the partial fulfillment of the Master of Computer of Applications degree during the academic year 2024-25. Approved By Prof. Anshi Shrivastava Dr. Rajnish Choubey (Prof. & Head)  ACKNOWLEDGEMENT At the outset, we express our deepest gratitude to Bansal Institute of Science and Technology, for providing us the opportunities and best facilities to work. We are grateful to DR. Rajnish Choubey, Professor & Head of MCA department under whose guidance we successfully completed our project and we are very much thankful to Anshi Shrivastava Mam for support and valuable suggestion. They willingly took the trouble of sparing his valuable time for our project and were always ready to help with his technical knowledge and valuable suggestions. We will be failing in our duties if we don’t acknowledge the valuable motivation and advice received from Dr. Damodar Tiwari Sir, Director-Bansal Institute of Science & Technology and our teachers in the institution from time to time. We express our heartfelt indebtedness to them. We also express our gratitude to all those who guided us and helped us in preparation of this project report. Last, but not the least, we are thankful to my friend who encouraged us by taking keen interest in our project work and directly or indirectly provided us their support. Ankit Verma (0112CA231020) Project Synopsis: Voice Assistant Project Title: Voice Assistant for Personalized Task Management Objective: The primary objective of this project is to design and develop a voice-controlled assistant capable of performing basic tasks such as scheduling reminders, answering general queries, controlling smart home devices, and providing personalized responses. The assistant will use Speech Recognition and Natural Language Processing (NLP) to understand user commands and respond appropriately. Introduction: Voice assistants have become increasingly popular due to their ease of use and accessibility. They utilize voice commands to perform actions, search the web, send messages, or control smart devices. The aim of this project is to create a custom voice assistant tailored to specific tasks like managing schedules, providing real-time information (weather, news, etc.), and interacting with users in a conversational way. Scope of the Project: This project focuses on: 1. Implementing Speech-to-Text functionality using a speech recognition library. 2. Processing user commands using Natural Language Processing (NLP) techniques. 3. Implementing Text-to-Speech (TTS) to provide responses. 4. Executing tasks such as setting reminders, fetching weather reports, controlling music, or managing a to-do list. 5. Expanding functionality by integrating APIs (e.g., Google Calendar API, Weather API, Smart Home APIs). Tools and Technologies: 1. Programming Languages: Python, JavaScript (optional for front-end). 2. Libraries/Frameworks: o Speech Recognition: speech recognition, pyaudio. o Natural Language Processing: NLTK, spaCy, or transformers. o Text-to-Speech: pyttsx3 or Google's Text-to-Speech API. o APIs: Google Calendar API, Weather API. 3. Hardware (optional): Raspberry Pi for integration into smart home systems, microphones, speakers. Page 1 of 3 Methodology: 1. Speech Recognition: o Implementing the speech recognition module to convert spoken words into text using Python's speech recognition library. o Processing audio inputs from the user and handling noise for accurate recognition. 2. Natural Language Understanding (NLU): o Using NLP to parse and understand the commands given by the user. o Classifying the user’s intent (e.g., setting a reminder, asking for the weather, etc.) and extracting relevant information. 3. Task Execution: o Based on the parsed command, the voice assistant will perform specific tasks like searching for information, setting reminders, or controlling devices. o Integration with external APIs (weather, news, calendar, etc.) to enhance functionality. 4. Text-to-Speech (TTS): o Converting the system’s responses from text back to speech using TTS, enabling a conversational experience for the user. 5. Voice Interaction Flow: o The assistant will engage in a natural dialogue with the user, providing feedback and asking follow-up questions if necessary. Expected Results: The result will be a fully functional voice assistant capable of:  Responding to voice commands.  Fetching information from the web.  Performing task management functions (e.g., setting reminders, alarms).  Controlling smart home devices if extended to include IoT integration.  Providing real-time information (e.g., weather updates, news summaries). Applications: This voice assistant can be applied in various scenarios: 1. Personal Task Management: Assisting users in managing their schedules and daily tasks. 2. Home Automation: Controlling smart devices at home (optional). Page 2 of 3  3. Information Retrieval: Answering factual questions and providing updates on the weather, news, or other data. 4. Accessibility: Assisting users with visual or physical impairments by offering hands-free control over devices and tasks. Conclusion: The Voice Assistant project will demonstrate the use of Artificial Intelligence, Natural Language Processing, and Speech Recognition to create a practical, interactive system that improves users' daily life by making task management and information retrieval more convenient. Future Enhancements:  Integration with Machine Learning for personalized recommendations.  Voice biometrics for user authentication and security.  Support for multiple languages and accents.  Incorporating Deep Learning techniques for improved speech and intent recognition. References:  Speech Recognition Library Documentation  Google's Text-to-Speech API  Natural Language Toolkit (NLTK) Page 3 of 3