https://github.com/munas-git/text-summarization-webapp
Extractive, Abstractive text/document summarizing system with Flask, capable of suggesting topics, detecting language, summary download and text-to-speech.
https://github.com/munas-git/text-summarization-webapp
abstractive-summarization css extractive-summarization flask gpt-3 html javascript language-detection language-processing natural-language-processing natural-language-understanding nlp open-source openai opensource opensource-projects opensourcedesign python summarization topic-modeling
Last synced: 11 months ago
JSON representation
Extractive, Abstractive text/document summarizing system with Flask, capable of suggesting topics, detecting language, summary download and text-to-speech.
- Host: GitHub
- URL: https://github.com/munas-git/text-summarization-webapp
- Owner: munas-git
- Created: 2022-07-19T14:15:25.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-11-28T20:14:44.000Z (about 2 years ago)
- Last Synced: 2023-11-28T21:44:03.873Z (about 2 years ago)
- Topics: abstractive-summarization, css, extractive-summarization, flask, gpt-3, html, javascript, language-detection, language-processing, natural-language-processing, natural-language-understanding, nlp, open-source, openai, opensource, opensource-projects, opensourcedesign, python, summarization, topic-modeling
- Language: CSS
- Homepage: https://doc-summary.onrender.com/
- Size: 28.7 MB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
#### Project Status: Complete.
> Access project Here. Click link or scan QR Code below. (Note: Site may take up to 45 seconds to load due to render free tier RAM allocation, SORRY about that 😥😅).
> ABSTRACTIVE SUMMARY FEATURE IS CURRENTLY DOWN.
# Project Title: Extractive, Abatractive document/text Summarizing System.
## Project Description.
The document summarizing system was done as my final year project in partial fulfilment of the reqirements for the award of Bachelor of Science B.Sc. (HONS) in Software Engineering at Babcock university.
It not just a summarizing system, it is also capable of predicting/suggesting highly accurate subject matters/topics of any body of text entered into it, providing users with the top 2 most likely topics.
The system is also capable of detecting the language of the body of text entered; Model was trained with data from here, and finally, it is equiped with a text-to-speech feature which reads the summary for users and a download feature which allows users to download their summaries as word (.docx) documents.
### Tools and Libraries used:
* CSS
* Nltk
* Docx
* Flask
* HTML
* Pandas
* JavaScript
## Snapshots of System.
## Demo of System.
https://user-images.githubusercontent.com/78413685/218328293-cc719537-90ed-4fff-9146-6095b641fe30.mp4
> Extra Notes
##### The system UI was a template gotten from free-css however, I made several adjustments in order to suite my taste and my project requirement. I'm currently not very good with HTML and CSS 😅.
##### There is still room for code refactor and system improvements. New features such as converting summary from one language to another, a broader vocabulary for word synonyms (one word having a list of signle word or phrase synonyms instead of single synonym and synonyms of non-english words), improved UI, better speach synthesizer, multiple download formats, support for more document type summaries, improved system security, improved language model performance (Collecting usser review on predicted review, saving response to db, automate model re-training and re-deploying process.) and more are updates in view however, you are more than welcome to fork this repo and make those changes and more 😉.