Python
Machine Learning and NLP
2023
ID: 1CP0677
Automatic Question Generation from Multimedia Content
Keywords:
Automatic
Question
Generation,
Natural
Language
Processing,
Video
Transcription,
spaCy,
NLTK,
POS
Tagging
Project Synopsis & Overview
This project develops an automated question generation system that creates contextually relevant questions from textual and video content. It extracts audio from videos, converts speech into text, and applies NLP techniques such as tokenization, POS tagging, named entity recognition, lemmatization, and chunking to identify key information. Rule-based question generation produces WH-type questions for educational assessment, self-learning, and interactive learning applications.
Complete Technical Specifications
| Project ID | 1CP0677 (DB ID: 677) |
| Project Title | Automatic Question Generation from Multimedia Content |
| Domain Division | Python |
| Sub-Domain / Tech | Machine Learning and NLP |
| IEEE Year | 2023 |
| Package Price | ₹6500 |
| Created Date | Nov 06, 2026 |
Project Price
₹6500
₹8000
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100% Executable Source Code & DB
IEEE Journal Paper Synopsis & PPT
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