Testing Machine Learning tools for optimizing the Steem

I've been very busy researching machine learning projects on GitHub and reading papers on optimizing the experience of writing, transforming, retrieval, evaluation and analytics of articles like those on Steem.

Problems I see for example with Steem is finding helpful and genuine comments. So sentiment analysis would be great for that. Also I'd love to see if my efforts paid off on commenting on great projects people propose or do, to invite them to the #BeyondBitcoin #Whaletank, a startup incubator you could call it...............

Multitrack editing with synchronization

ag non-lexical utterances

We also want to make our podcasts nice and speedy for our listeners so what is needed is a method to catch Part-of-Speech (POS) utterances like

um", "er", "ah", or other vocalisations for reasons that linguists are not entirely sure about.

Yeah coming from the Register, I'm sure they are not sure about many things. Like starting at the bsic question that you'd maybe not ask linguists but rather neuroscientists?
And automagically filtering them out to make podcasts' duration shorter..................