Voice to text is a multi-million if not billion dollar endeavor. I simply implemented the Web Speech API, which ostensibly uses Google (and possibly Apple's) voice recognition system. I came up with the text comprehension bit, which is limited to the input quality (what I get from the API) and the training set. I've been adjusting and adding to the training set since I first released this, but the matching has worked as well as I'd hope for.

My training set is specifically designed to be conversational interview and personal questions, but I think a lot of the people who reach the site don't grasp that.

Here's some examples of the input it gets and has no clue what to do with:

- " um changes nice so when you change the things december " matched to: -1: no match

- " nexus 10 " matched to: 13: Huh?

- " pictures " matched to: 14: Huh?

- " call " matched to: 17: Cool

- "videos " matched to: 16: Huh?

- " change " matched to: 15: Huh?

And this is a set of input where people did get it:

- " hi what's your name " matched to: 23: My name

- "what's your name " matched to: 27: My name

- "what do you do " matched to: 31: What I do

- "why should we hire you " matched to: 38: Why you should hire me

-"what's your favorite food " matched to: 35: Food

-"wendy's see yourself in 5 years " matched to: 28: Goals