I am exploring the idea to create a fast, reliable crowd-powered method to accurately transcribe lectures. This has been well-explored in the past and fortunately due to Google’s auto transcription we have a fairly easy way to extract near-perfect descriptions – the draft for yesterday’s workshop is here.
For starters, one powerful use-case is the search functionality this doc can provide. For instance, I can quickly retrieve places where @jeremy is talking about list comprehension. However, the document is far from perfect – there are typos – some innocuous and a few others which may potentially impede the reader’s thought-flow. Here is a sample :
10:03, your laptop probably doesn’t have they
10:06, deep learning compatible GPU in it this
10:09, is something and you know most people I
10:11, know including most of the most serious
10:12, researchers in breakfast
10:13, used AWS for most of their work back so
10:18, that’ll make you you know it’s a kind of
10:21, getting familiar with AWS is something
Looking for suggestions on systematic ways to clean this. Ideally, it would be great to come up with a method which can work for all future lectures. We can probably add the improved version to the wiki thread. Happy learning!
A transcription of each lesson would be much appreciated. They don’t need to be time-coded at all - YouTube does that automatically. In the previous courses @lin.crampton was kind enough to transcribe the whole lot! Some kind of more crowd-sourced approach would be cool. It’s important for students where English isn’t their first language, and of course for those with hearing difficulties.