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Speech Recognition Is Not Solved

awni.github.io

81–90 of 208 posts

Re: Speech Recognition Is Not Solved

#81

Earlier quoted context omitted.

I'd never heard of APD. Interesting, all my life I've struggled to follow a conversation in a crowded environment, so much so that I actively avoid background noise with words in, I work with silicon ear plugs in or headphones and music with no lyrics. Looking at NHS symptoms they describe me as a child, didn't learn to read until I was 8. I nearly ended up in the remedial track but for a single awesome teacher who s…

Wow, I wish there was an easy way to pay back star teachers or mentors.

The best way to pay them back is to succeed, but it's not easy!

Re: Speech Recognition Is Not Solved

#82
post #74

Earlier quoted context omitted.

I'd challenge you to transcribe a casual conversation without understanding. Too many words sound very similar, if not identical, and the context of the conversation dictates which word is in play. Even something simple like "They're unhappy, Ness" could be interpreted as "Their unhappiness" unless you know Ness is a person in the converation.

That's like saying because "O" and "0" have the same shape that we can't solve OCR without general AI. A modern statistical speech recognition system has no trouble determining that "they're unhappy, ness" is a dramatically less likely word sequence than "their unhappiness". edit: I read your example backwards, but still, a statistical system can easily incorporate contextual words without actually understanding what…

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Re: Speech Recognition Is Not Solved

#83
Do you guys thing “understanding” needs more that what we have right now in terms of AI, does understanding require intelligence that is self aware? I mean when we talk to each other, we understand in spoken words, little expressions, even when we talk over the phone. I feel like without the ability to process emotion and self-aware AI we wont really achieve “full understanding” only simulated ones.

Re: Speech Recognition Is Not Solved

#85
post #36
post #13

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I too would be interested in pointers to the leading open source options. Just yesterday there was a Show HN built with the https://github.com/kaldi-asr/kaldi project, emscripten-ized: https://news.ycombinator.com/item?id=15534531

When I looked a while back, CMUSphinx seemed to be the most promising option but I struggled to get it installed and got distracted with real work. Some discussions online suggest it’s still fairly poor compared to the online engines. Snips was mentioned here recently but I haven’t taken a look at it.

I had a working cmusphinx setup at one point. It was so bad that I eventually just tore it down.

It showed promise, but I don't know if any work is being done on it.

Re: Speech Recognition Is Not Solved

#86

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> Since then I've thought about voice recognition differently. The AI to understand the context or fill in the blanks is what will make or break it. Of course, and all humans rely on this as well. No one hears every word perfectly all the time --- it's impossible, because the source person doesn't pronounce every word perfectly all the time. Context clues are a huge part of speech recognition, as well as gestural typ…

This is why I think Google recently saying 95% word accuracy is just as good as a human is wrong. If I ask if you after dinner if you "Want to get a pizza cake", you'll probably quickly realize I mean "piece of cake". Mistakes like that in 1/20 words is a lot. Google is the best of all the big players at figuring out this context (I once asked it what a Dead Left Shrimp was, apparently I was mishearing the name of ba…

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Re: Speech Recognition Is Not Solved

#87
post #23

I think some people overestimate how good humans are at speech recognition. Unfamiliar accents and noisy environments cause havoc with many people. I had a friend who learned English in India when I was in High School, so I was used to that accent; many of my classmates in College could not understand anything our Indian T/A said freshmen year. Similarly I had friends for whom English was a second language who had li…

I agree with your point. It can be hard for a US native English speaker to recognize a Scottish accent. But, other Scottish people certainly don't have trouble with understanding a Scottish accent. So I view that as a certificate that we should be able to build a speech recognizer which can recognize Scottish accents.

> But, other Scottish people certainly don't have trouble with understanding a Scottish accent. So I view that as a certificate that we should be able to build a speech recognizer which can recognize Scottish accents.

As a Scottish person, I'll say there's a huge amount of variation between Scots dialects. As someone who grew up in Fife, it took me well over a year of living in Glasgow to be able to reliably understand people there—and both of them are typically classed as Central Scots.

Re: Speech Recognition Is Not Solved

#89
I am a native English speaker from California. It is hard to get my Google Personal Assistant to understand the difference between desert and dessert. It's also hard to request music by an artist with name similar to another artist.

"Hey Google, play Mika radio" has a 50/50 chance of starting music by Meiko. The additional "problem" is that I like Meiko, too, but I feel obligated to cancel the Meiko music & re-request Mika so that Google (hopefully) learns to recognize the difference between Mika and Meiko.

Maybe our spoken language will start to transform into distinctly unique sounds so we can verbally interact with computers with relative ease. When I was in the US Army, I was trained to speak in a certain manner to help my communication to be more clear. [1] I don't see a reason humans and computers can't each make reasonable compromises to make verbal communication easier.

[1] https://en.wikipedia.org/wiki/Voice_procedure

Re: Speech Recognition Is Not Solved

#90
post #74

Earlier quoted context omitted.

I'd challenge you to transcribe a casual conversation without understanding. Too many words sound very similar, if not identical, and the context of the conversation dictates which word is in play. Even something simple like "They're unhappy, Ness" could be interpreted as "Their unhappiness" unless you know Ness is a person in the converation.

That's like saying because "O" and "0" have the same shape that we can't solve OCR without general AI. A modern statistical speech recognition system has no trouble determining that "they're unhappy, ness" is a dramatically less likely word sequence than "their unhappiness". edit: I read your example backwards, but still, a statistical system can easily incorporate contextual words without actually understanding what…

That's because it doesn't care, it just goes for the most statistically probable phrasing in a general conversation, not the one you're actually having.

As for the OCR problem, try writing one for Chinese calligraphy and get back to me on if context is important or not.

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