Project Code and Documentation of Natural Language Processing Based Question Answer Engine from Videos

By: Prof. Fazal Rehman Shamil
Last modified on May 1st, 2021

Natural Language Processing Based Question Answer Engine from Videos

Project Domain / Category

Artificial Intelligence: Natural language processing, Speech recognition, Computer Vision

Abstract/Introduction

Automated question answering from lecture videos material will use in aggregation with PowerPoint slides that system will be built by using Natural language processing (NLP). In this system, it will be considered requirements that utilize logic to locate, extract, and represent a specific answer to a user question expressed in natural language (English). A QA system would take as input a question and it should get as output. For the online scenario, students will ask questions to an Instructor captured in the video.

Functional Requirements:

  • The application should have a graphical user interface that has an admin interface
  • The Admin should be login with a valid username and password.
  • Admin should manage all activities of input and output parameters on the GUI interface.
  • There are seven major tasks you will typically perform when developing a system. Tasks (2-7) should be implemented internally while developing the system.

Task 1: Define the problem

Task 2: Question Processing

Task 3: Answer Extraction

Task 4: Video Preprocessing

Task 5: Build system

Task 6: Test System

Task 7: Tune System

    • The application should have a knowledge-based system and have added phonetic-based transcript error correction, and enhanced video transcripts with the text from the PowerPoint slides.
    • The application should have reports management
    • The admin should manage and view all backup records.
    • The admin should view the performance and update knowledge based on the requirement.

Note: Skype sessions must be attended to communicate with the supervisor about AI approaches otherwise project will not be accepted.

Tools:  Python language

Tools will be recommended by supervisor like speech recognition etc

Prerequisite: Artificial intelligence and Natural language processing Concepts, students will cover a short course relevant to the mentioned concepts besides SRS and design initial documentation.

class diagram, activity diagram, data flow diagram, sequence diagram, use case diagram, testing test cases, SRS document and others are need to draw for this project.

Class diagram, activity diagram, data flow diagram, sequence diagram, use case diagram, testing test cases, SRS document and others are need to draw for this project.

Prof. Fazal Rehman Shamil