Logic 1.3

1. Start
2. Invite digital twin of note taker to online meeting (we have to create meeting link  with date and time and create a schedule then at the specified time note taker will hit link.)
3. Participate in online meeting like other members
4. Record the meeting
5. Prepare notes as verbatim(speech to text transcription)
6. If during speech to text conversion during online meeting if it failed to convert then it can be corrected by raising an error or asking doubt to attendee(such as i didn't understand ,can you repeat this)
7. During Speech-to-Text, you can provide a list of additional languages that the audio data might include If you include a list of languages in your request, Speech-to-Text attempts to transcribe the audio based upon the language that best fits the sample from the alternates you provide Speech-to-Text then labels the transcription results with the predicted language code this way notetaker can deal with multiple languages during meeting.
8. Detect important keywords based on agenda
9. During the meeting if notetaker detect that screen is being shared or any thing is being presented then it automatically switches to video recording and screenshot of screen.
10.Identify the content of the images/graphs 
11. Time stamp and speaker recognition has to be done(Time stamp can be achieved by speak diarization, Speech-to-Text can recognize multiple speakers in the same audio clip.)
12. If there is any special notes to be taken more importantly we can use a special assist called upon a keyword (If coffiecient of Relation crossed a certain fixed threshold then it is consider as important keyword as soon as these keyword are detected then it will start recording.
)
13. All the data will be saved in the drive with audio and video clips for future uses
14. After Speech to text  summarization of meeting has to be done
 can be done by taking the text splitting into sentences ,removing stop words, and other text preprocessing ,building a similarity matrix, finding their rank and picking top
 sentences from matrix. 
15.Text detection has to be done from the images shown in the screen
16. End.