Design project by-vitul-chauhan

1. Writers
Assistant
Tool

2. Team
Presentation
By:
2
Muvvala Sai Phanindra
STUDENT
Roll-No-18132003
IT-Gen/HITS
Vitul Chauhan
STUDENT
Roll-No-18132023
IT-Gen/HITS
http://vitulchauhan.site/

3. Introduction
as a student of the
Computer engineering
Discipline:
👉Too much writing takes too long.
👉 It makes you focus less on what
you’re writing, and instead you paint
letters on a page perfunctorily.
👉
Facts:
👉 Did you know that an average
person’s handwriting speed is 13
words per minute, and their typing
speed is 3 times greater.
👉
3

4. “
The goal of this project is
to implement technique in
a way which allow the
user to feed samples of
their own handwriting and
use those instead .
4

5. Advantages
👉 This tool we are going to decrease wastage
of human effort upto a particular extinct and we
can rather use this time saved to any knowledge
improving tasks.
👉 Basically this tool converts text content to
an image /Pdf that looks like handwriting

6. 6
👉 Different
Modules :

7. Phases
Letter Parser :
👉 Responsible for
getting input field
as Raw text, and
arrangement of a
letters is handled
here.
Line Parser :
👉 Responsible for
adding Proper
margin, padding
and text alignment .
Page Parser :
👉 Responsible for
Font size ,Ink
Colour, Page size
,Resolution, and
effects.
7

8. Phanses
Document Parser:
👉 Responsible for
adding background
images.
Processing :
👉 Responsible for
Converts letter text
to handwriting text.
Result :
👉 Responsible for
compiling pages
into a document for
downloading as
single documents.
8

9. Result
9

10. summarize
Automatically summarize any article, text,
document, webpage or essay in a single click.
10

11. Too long ? can't read?
There's so much
content out there but
too little time to read.
So many times, it
happens that there's a
long article that we're
interested in,
You can also split your content
but we don't really
feel like scouring
through it to extract
relevant information
from it.
11

12. Article Summary:
➜ Return a shortened hand copy to read items.
➜ Take a painfully long piece of text and sum it
up into key bullet points using the power of
NLP and A.I.
➜ It spend less time reading counterproductive
stuff and more on doing valuable work.
12

13. Summarize
Articles, News,
Anything
It uses AI to automate
this process, generating
multiple lengths so you can
get a summary,a 25% and a
50% view of the document.
13

14. It uses AI to
automate this process,
generating multiple
lengths so you can get a
summary,a 25% and a
50% view of the
document.
14

15. 15
Word cloud :

16. 16
Fish Bone diagram :

17. 17
UML :

18. 18
Class Diagram :

19. 19
Sequence Diagram:
:

20. 20
Text to Voice: Text to speech:We all know listening is more comfortable than reading
for us. For example, majority of us is more interested in watching biopic or listening
audiobooks than reading biography books. This tool helps user enter long paragraphs
and listen them comfortably.

21. 21
Quick reader:: Quick reader tool will preview words with large size that helps us to
read more comfortably and quickly without stressing our eyes much.in this tool we can
change preview speed, number of words displaying in the preview.

22. 22
Drawings Clipboard: Clipboard is like a sticky notes that can help you to paste
important or key points or bulletin points while researching and we also use it to
draw what is on our mind visually.
Board :

23. 23
To do list: To do list contains our schedules and time tables and
reminders as per our wish

24. 24
Text Summarizer :

25. 25
Word counter:Word counter will take the provided content and displays the number of paragraphs,
sentences, words, characters and approximate reading time of that particular content. This gives an
overall idea about the content to user.
:

26. 26
Research paper Reader:Research paper search: Used to search some reference
for our content development. Here we can directly search our topic related research
papers.

27. 27
Handwriting generator:

28. 28

29. References:
[1] Alex Graves.(2014).Generating Sequences With Recurrent Neural
Networks.Cornell University.https://arxiv.org/abs/1308.0850
[2] Alex Graves.(2014).Generating Sequences With Recurrent Neural
Networks.Cornell University.https://arxiv.org/abs/1308.0850
[3] Alex Graves.(2014).Generating Sequences With Recurrent Neural
Networks.Cornell University.https://arxiv.org/abs/1308.0850
…….…Thank You…………