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K.HARSHITHA 1602-21-735-014
TARUN 1602-21-735-051
M.VAISHNAVI 1602-21-735-056
Techstack
PROBLEM STATEMENT:
"In the context of enhancing collaboration, productivity, and information retrieval in a digital workspace, we aim to develop an integrated solution that leverages Natural Language Processing (NLP) and Computer Vision technologies. The primary objectives are as follows:
Text Summarizer using Transformer Model: Develop a robust NLP-based text summarization system powered by a state-of-the-art transformer model (Hugging face) to automatically condense lengthy textual content into concise summaries. This tool should be able to handle various types of textual data, including documents, articles, and reports.
Virtual Board with Computer Vision Canvas: Create a virtual collaboration platform with a computer vision-powered canvas that allows users to interact visually with digital content. The canvas should enable users to draw, annotate, and manipulate digital objects, making it a versatile tool for collaborative work, presentations, and brainstorming.
This problem statement clearly outlines the goals, challenges, and expected outcomes of the project, providing a roadmap for developing the NLP text summarizer and the virtual board using computer vision technology.
*Jupyter notebook
*Anaconda cmd
*NLP(trabsformers)
*Open_cv
*canvas(computer vision)
*Python
*Git(reposit)
Enhancing Collaboration and Productivity
Information Overload
Advancements in NLP and Computer Vision
User Experience
1.Input Text
2.Tokenization
3.Embedding
4.Transformer Model
5.Encoder (Text Understanding)
6.Attention Mechanism
7.Decoder (Text Generation)
8.Length Control( nucleus sampling)
1.Camera Setup:
2.Computer Vision Software
3.Object Detection
4.Perspective Transformation
5.Image Processing
6.Feature Extraction
7.Canvas Rendering:
8.Overlaying the Content.
1.Content Curation:
2.Search Engines:
3.Document Summarization
4.E-Learning:
5.Business Meetings
6.Interactive Whiteboards
1.Content Quality:
2.Abstractive Summarization
3.Scalability
Abstract
In this project we are develop a virtual board and text summarizer for smart
learning and teaching.virtual board is builded by using computer vision by
importing packages from mediapy(OpenCv).virtual board actually uses hand
tracking algorithm and develops the virtual board by importing aircanvas
technology for gesture recognition.
Text summarizer would take a audio as input and convert into a text or a
direct text and convert the text into summary points.NLP is used in text
summarization to analyse and understand the content of input text, score
sentences or phrases for importance, and generate coherent and concise
summaries. NLP techniques are used to preprocess the input text. This
involves tasks like tokenization and stemming of the input text.NLP algorithms
assess the importance of sentences or phrases within the text. Various
methods are used for this, including TF-IDF