[ereyes01]

IMO this article betrays a bit about why and how the author has come to be a fast talker. It has to do with how he distills the information and presents it to the reader.

The article explains a really cool application he put together to automatically transcribe his conference talks and measure the words per minute that he speaks. The problem I see is that he feels it necessary to describe his whole thought process and all his dead ends to arrive at his solution... i.e. he started with ffmpeg, pydub, and SpeechRecognition, then later turns out he didn't need pydub, then later he discovers he misconfigured SpeechRecognition because it was sending a ton of data to an external API, etc.

While this might be mildly interesting, I think the writing would be much more effective without all the dead ends and the spurious details that don't contribute to the thesis.

I am often guilty of not communicating in a simple and effective manner (rambling too much), and thus I tend to speak much faster than I need to due to the sheer amount of content my rambling introduces. This usually works against the goal of communicating effectively with my audience.

I realize I'm trying to project my own perspective onto the author, but I think there is a good chance that a great first step for him might be to simplify and distill his content before he speaks somewhere. This requires more preparation, but it greatly improves the end product (the public speaking).

[bcatanzaro]

I felt the same way. Especially when he measured "information" in his talks as a function of the number of words he said. I feel sorry for audiences who have to sit through talks where the speaker believes that the utility of the talk is linearly proportional to the number of words in it. Betrays a profound lack of empathy for the audience, and a lack of understanding of the purpose of a talk.

[jobigoud]

This reminds me of the research on comparative speed of different languages that ended up finding that the information density was essentially the same for all languages, even if the number of syllables enunciated per second was different.