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Speech Recognition Is Not Solved

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Re: Speech Recognition Is Not Solved

#31

Post by aidenn0 »

twothamendment wrote: post #27
aidenn0 wrote: 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 had a chance to live in the middle of the "hood" in a large American city for about 6 months. I was one of the few white guys around. I spoke English, they spoke English - but it was about a week before I could understand people, especially on a crowded city bus. The first few days felt like a foreign country and it was the same country I grew up in! I wonder how well Siri and friends work with Ebonics?

That's a double whammy because diction is so different as well; our brain fills in the gaps in phoneme recognition by pattern matching and the differing dialect makes that much harder as well.

Re: Speech Recognition Is Not Solved

#32

Post by dragontamer »

ddevault wrote: post #8
johnramsden wrote: post #6

What I would like to see you would be an open source speech recognition system that is easy to use, and works. There is really no match for the proprietary solutions in the open source world right now, and that is disappointing. Not to say that there aren't open source speech recognition systems, they just aren't completely usable in the way proprietary solutions are. A lot of research goes into open source speech re…

I agree - I don't care how good Google gets it, this is an unsolved problem until I can do it with open source tools operating without an internet connection.

Google has basically invented a special processor with a very, very, VERY weird architecture for these sorts of tasks: https://drive.google.com/file/d/0Bx4hafXDDq2EMzRNcy1vSUxtcEk...

I don't think this level of computational power can be achieved on a modern CPU, or even a GPU! But GPUs are probably the closest analog to Google's absurdly parallel architecture.

To get a GPU working at maximum performance, you either have to go OpenCL2.0 or CUDA. Compared to OpenCL1.2, OpenCL 2.0 has a better atomics model, dynamic parallelism (kernels that can launch kernels), shared memory, and tons of other features.

NVidia of course supports those features in CUDA, but NVidia's OpenCL support is stuck at 1.2. So in effect, CUDA and OpenCL are in competition with each other.

Anyway, that's the current layout of the hardware that's available to consumers. I think its reasonable to expect a graphics card in a modern machine, even Intel's weak integrated-GPUs have a parallel-computing advantage over a CPU.

So for high-parallelism tasks like audio analysis or image analysis, it only makes sense to target GPUs today.

Re: Speech Recognition Is Not Solved

#33

Post by pjc50 »

aidenn0 wrote: 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…

Obligatory "voice recognition lift in Scotland" comedy sketch: https://www.youtube.com/watch?v=sAz_UvnUeuU

Personally I've had to "translate" between a South African and an Ulsterman before, both of whom were speaking English but with extremely different accents.

Re: Speech Recognition Is Not Solved

#35

Post by rav »

theresistor wrote: post #18

Speech recognition for multi-lingual speakers is another pain point. I live with a native French speaker, so my conversations naturally include a lot of French proper names, as well sometimes switching languages mid conversation or even mid sentence. Lots of recognition engines can handle English and French, but treat them as mutually exclusive. It frustrates me to no end when I know that Siri can recognize a French…

As a multi-lingual speaker I've even had problems with speech synthesis. For instance, Google Maps insists on narrating driving directions in the system language, which is set to English; this makes the narrated local non-English place names incomprehensible. If I succumb and change the system language I can understand the narrated place names, but in return I have to put up with the poor speech synthesis of non-English languages.

Re: Speech Recognition Is Not Solved

#36

Post by ghaff »

j_s wrote: post #13
johnramsden wrote: post #6

What I would like to see you would be an open source speech recognition system that is easy to use, and works. There is really no match for the proprietary solutions in the open source world right now, and that is disappointing. Not to say that there aren't open source speech recognition systems, they just aren't completely usable in the way proprietary solutions are. A lot of research goes into open source speech re…

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.

Re: Speech Recognition Is Not Solved

#37

Post by dmreedy »

Of course it's not solved. We don't even know how to define the problem.

Speech is[1] a fundamental component of Language, which is a fundamental component of Intelligence[2]. This is addressed somewhat in the conversation around semantic error rate; that there is more to processing raw audio speech than the calculus of mapping signals to tokens; some understanding of semantics and context is required to differentiate between otherwise indistinguishable surface forms.

I find it doubtful that there's a clean interface that separates the 'intelligent' parts of the brain from the 'language' parts of the brain from the 'speech' parts of the brain. This leakiness (or richness, really) means that you can't neatly solve any one part of this chain to the level of competence that the brain solves it. That means to 'solve' speech recognition, you have to 'solve' language, and thus 'solve' general intelligence. And to 'solve' general intelligence, you have to understand it, in a theoretical sense, which we don't. Indeed, it will likely involve solving all the other modalities of sensation as well. It's definitely the case that you need to have a model for prosody to understand speech. It is entirely possible that vision is a large factor as well, in the form of body language, lip reading, eye contact, and so on.

Speech recognition is quite good for what it is. For many practical applications, especially to do with young, white, newspeaker-accented English speakers who sound the most like the people who develop it, and the data sets used to develop it, it is good enough in the 80/20 sense. But it is nowhere near solved by even the least rigorous definition of the word.

----

[1] according to the philosophy I subscribe to, at any rate

[2] according to the philosophy I subscribe to, at any rate

Re: Speech Recognition Is Not Solved

#38

Post by morinted »

tyingq wrote: post #25
morinted wrote: post #22

I'm part of the stenographer/captioner community as a hobby and you'd be surprised at how many people think that all captions are automatically computer-generated. In reality the practical limitations of autogenerated captions are demonstrated by YouTube's caption system. It's good but even a mistake every other sentence (95%+ accuracy) can completely obfuscate the meaning behind the video.

I've seen some pretty terrible human produced captions on television shows as well.

Big time. There are various levels of caption quality and part of it is the tools used.

1. QWERTY transcriptionists working brief, 5-10 minute shifts typing as fast as they can and rotating.

2. Voice-mask reporters using Dragon with a voice mask (more commonly phonetic typos)

3. Stenographers using a steno machine, some of them were not trained to do realtime and lack the ability to edit as they go.

It's all up to the individual, unfortunately. Furthermore, the budget for live captions is sometimes smaller than it should be and so the service purchased is the cheapest, not the best.

I pay attention to captions now. I've watched TSN (Canada) and it seems that past 10 p.m. they put in someone who isn't fully trained or graduated from school and they most definitely shouldn't be providing captions as they are near unreadable.

Good captions are priceless for the access that they offer.

Re: Speech Recognition Is Not Solved

#39

Post by throwmenow_0140 »

joemag wrote: post #21

Mistakes in understanding speech are common even among humans. My wife and I have to repeat and clarify ourselves fairly frequently in our day to day conversations. She even jokes at times that I must check my hearing, because I often mishear what she said, while she thought she was being perfectly clear. I think where computers fall short is in two areas: 1) The rate of errors hasn’t hit the inflection point of bein…

"Please, hand me a tractor" - Did she say tracker [1]?

Something like Rhymezone (searching for similar sounding words) would be a solution. It would still need a human who's deciding which word to choose, but after some time it could learn which words you prefer.

[1] https://www.rhymezone.com/r/rhyme.cgi?Word=tractor&typeofrhy...

Re: Speech Recognition Is Not Solved

#40

Post by notahacker »

Radim wrote: post #19

Just the other day, I participated in a discussion about how "language identification" is a solved problem -- in fact, hasn't it been solved for a decade? As anyone who's had to use langid in practice will testify, it's solved only as long as: A) you want to identify 1 out of N languages (reality: a text can be in any language, outside your predefined set) B) you assume the text is in exactly one language (reality: c…

I'm reminded of how often I see Twitter offer to translate English-language tweets containing a proper noun or two from absurdly unconnected languages. And that's with text containing mostly common and distinctive English words.
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