> If that quote attributed to Fred Jelineck ("Every time I fire a linguist, the performance of the speech recognizer goes up") is right, they should have negative linguists.

That's a really, really, really stupid quote that pushes the increasingly popular world view that experts only drag the world down on every subject.

Linguists' contribution is unrelated to performance, positive or negative. Performance is the job of computer scientists designing architecture and of skilled programmers doing smart implementations of architecture.

The performance would probably go up if the company fired all presidents/vice presidents/CFOs etc., too (giving implementors free reign, unconstrained by costs and schedules), but the company would probably go under.

Every specialist has their own role to play. Thinking that subject domain expertise is a negative is indefensible.

Just to add my two cents (I work for Mozilla on Common Voice): without help from linguists, Common Voice would have made some very different and very bad decisions about all sorts of things like: accents, dialect segmentation, corpus curation, licensing, and many other things. Linguistics were absolutely instrumental. We tried to thank some of them at the end of our blog post: https://medium.com/mozilla-open-innovation/more-common-voice...

I think you are misinterpreting the quote. He meant that experts (computational linguists and statisticians) had a firmer grasp of the task of inference in language than linguists, who tend to care more about formal structure (i.e. Chomsky's competence/performance distinction) and are less aware of problems like overfitting. If anything, it's stressing the importance of domain expertise, just suggesting that who those experts are may be nonobvious.

Thanks for explaining. I would then say that a quote that actually means the opposite of what it appears to mean is a stupid quote for other reasons.

Even with the explanation, it still comes across more as blaming the linguists than the people who assigned the wrong people to the wrong tasks.

(Why are they fired rather than reassigned? Why were they ever hired if they're the wrong specialty and aren't needed elsewhere?)

And if you blindly follow the machine learning path with no scientific context you will convince yourself that having negative people on a team is an answer that makes total sense.

I worry about this in a lot of fields where we are heavily pushing machine learning. I was also not saying that this project is somehow poor quality, I just could not find much about the team and was curious about their research backgrounds.

Hello, sorry to interrupt the conversation. I am Alireza. I am the founder of Picovoice (maker of Cheetah).

Thanks for mentioning the quote I heard it from few friends who used to work in Nuance. But didn't know where it came from originally.

We have a very small engineering team who deeply understands machine learning and (embedded) software. I have invented/co-invented few US patents in speech processing/recognition prior to Picovoice. But have no academic background in linguistics. Having worked with computational linguists, they are definitely a solid plus to the team when their skill set is utilized correctly. I appreciate your question and curiosity. We hopefully will provide more information about the team on our website soon. Thank you.