Requirements NodeJS v11.4.0 or above.

$ npm install 

$ npm run develop

1. Bump version npm version [major|minor|...]
2. Git push git push && git push --tags
3. Deploy npm run build-and-deploy to ELECT's gitlab.
4. Ping P'Tai in Slack

Date	Status	Links
2019/07/25	Completed
2020/02/24-27	Completed

• Use machine learning algorithms to automatically identify speakers in each part of meetings. From what I see, this scenario is probably a Blind Source Separation problem. Hence, we might start with Independent Component Analysis (ICA).

Apart from being a tool that provides an efficient way to listen to parliament meetings, its datasets are also valuable. These datasets could results in several applications including:

1. Performance metric of each member of parliament (MP). Althought it's a rough estimation, having this metric would allow people to see how their representatives perform.
2. Inspired by the famous online game Fantasy Football, we could build Fantasy Politics in which people will play by picking a squad of politicians before next meeting. How members in the squad participate in the meeting will result scores that the player will receive after the meeting.
3. Inspired by music streaming services, i.e. Spotify or Fungjai, we could have a similar platform, Fungkai Dee, offering tracks of politicians talking in parliament meetings.

• This projects was bootstrapped with Gatsby.

The code is licensed under the MIT License

Data is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0)