4 ms·

On Speech Recognition: Pointers for Newbies & Lessons from a failed startup

18 points by fjabre 17y ago

mahmud 17y ago
As real and raw as anything written by a badly bitten practitioner. If you're doing SR, don't read this article and don't bookmark it, wrecking a nice beach takes a lot of fucking effort; just contact the author and grab the guy while he is between gigs. If I had the money I would be hiring these guys with "failed" startups and pairing them with good sales people. They haven't failed, they just don't have industry contacts :-(
deleted 17y ago
[deleted]
henning 17y ago
My guess is that if any of this was new to you, it should be a clear sign you have no business doing a company in this niche.
- fjabre 17y ago
  Is that to say Mark Zuckerberg shouldn't have done a social networking site or Steve Jobs, Pixar..? In fact maybe anybody who has their bachelor degree in liberal arts shouldn't even dream of going to med school or being a lawyer. This line of reasoning is flawed. Some of the most successful people I've met in life have ended up doing things they never would have imagined.
Caligula 17y ago
Long 5am post alert broken into sections corresponding to the authors. I wish I read this 8 months ago so it could of prepared me for some of the misery to come. I initially thought it would be simple. Use some of the open source tools or commercial SDK's, then quickly move on to the important stuff. Did not turn out that way. In fact, speech recognition is a time killing whore, but it sure is interesting, sometimes at least. 1. Telephony & VoIP: I disagree with the author. Freeswitch comes with speech recognition built in and recently added uniMRCP so I think FS is definitely better not even taking into account how shady asterisk is. The prices he lists are also on the high side. You can get local DID's for half what he lists, probably further less in bulk. 2. Web Services: Agree with his comments on web services. Speech recognition is perfect for scaling onto the magical cloud. Dictation is more difficult because for very large vocabulary at least, your going to take up a system to process it and be lucky to get 1RT. 3. Embedded Disagree with this. Some decoders are made specificially for this. Well pocketsphinx is. It even used ARM ASM code to speed up calculations on embedded devices so you can get better results on the iphone for example. The developer for pocketsphinx for example recently made this fantastic demo for the N800 which I recall was similar to the iphone in power. http://www.youtube.com/watch?v=OEUeJb6Pwt4 http://www.youtube.com/watch?v=OEUeJb6Pwt4 And I am sure it can be tweaked to be even better. So much of speech recognition is tweaking. As he states correctly, Lumenvox is based on sphinx(sphinx2 I recall reading), just its very tweaked. Commercially available: Very funny, I agree with most. MS,AT&T,IBM suck at least for providing API's but their tech is very good. IBM for example released theirs as opensource but changed their mind and just let it die. Nuance is 'contact our salesperson' expensive. Lumenvox is the most affordable. Open Source: Minor nitpick, he should of included HTK with Julius. Acoustic models definitely have given me the most grief. I use sphinx4 and pocketsphinx and am very pleased. They are state of the art decoders. The acoustic model, or lack thereof is the reason why commercial engines are perceived as superior. If you have 50k you can spend get a LDC membership with tonnes of transcribed data. Slap it into the trainers format, BAM. Unfortunately I was not going to do this. I disliked the LDC for what I thought was gauging. Same prices for mega corporations as individuals. But after making my own model, and still in the neverending process of making my own, tweaking it, etc.., I appreciate the misery that is collecting and organizing transcribed data and appreciate the work they do even if I can't use it. Notice something wrong with your model, need to retrain it. Takes days with a quad core. In fact my new 8core beast of a server I ordered arrives next week, I wonder how my parents will take the noise, apparently servers are loud. Even with that it will take maybe half a day. And spotting errors is hard. I cant emphasize enough how boring it is to listen to hours on end of audio and see that it matches up with the text perfectly. In some cases, listening a bunch of times to make sure. Noticing issues with your model, having to go figure out why. Voxforge.org is great. They have ~50 hours of quality data, most at 16khz computer microphone but a good portion at 8khz telephone. You can always downsample. But for dictation you need much more. You dont need thousands of hours unless your doing dictation and if that extra few percent is worth it. You can get good results with low hundreds. There are other equally important factors like language models that he should of mentioned that could be equally as important as the acoustic model. How its important to have relevant, and lots of data to train them. The acoustic model is only one of many factors(as is the decoder for the matter). Perhaps because its that he did not focus on dictation that he left it out. Wrapping Up: FS better. At least try both, its trivial to set each up and follow a simple tutorial. You can still plug lumenvox into FS, although it will cost. But it would cost the same for asterisk. I agree that its difficult but I don't think that should stop you. Just be aware its a lot of work, some of it very boring and frustrating, but I am sure the same can be said for most things. Ok maybe not :)
danbmil99 17y ago
he starts out saying "stay the fuck away from this stuff" then goes on to talk lovingly of the tech. WTF? Where's the explanation of why it didn't work as a business? I think the OP is a bit too in love with the technology, that's probably why he got burnt.
- mbrubeck 17y ago
  And he said exactly that in his previous post: "So the number one reason my startup failed was: I was distracted by a cool and shiny feature that didn’t solve anyone’s problem." http://www.teabuzzed.com/2009/08/the-number-one-reason-my-startup-failed/ http://www.teabuzzed.com/2009/08/the-number-one-reason-my-st...
fjabre 17y ago
BTW just to clarify: by all means integrate speech rec into your solution if you feel you get a real value proposition by doing so. For my product it wasn't really needed and was more of a distraction than anything else. However I learned so much in the process I wanted to share this back with the community.

18 points by fjabre 17y ago

As real and raw as anything written by a badly bitten practitioner. If you're doing SR, don't read this article and don't bookmark it, wrecking a nice beach takes a lot of fucking effort; just contact the author and grab the guy while he is between gigs. If I had the money I would be hiring these guys with "failed" startups and pairing them with good sales people. They haven't failed, they just don't have industry contacts :-(

deleted 17y ago

[deleted]

henning 17y ago

My guess is that if any of this was new to you, it should be a clear sign you have no business doing a company in this niche.

fjabre 17y ago
Is that to say Mark Zuckerberg shouldn't have done a social networking site or Steve Jobs, Pixar..? In fact maybe anybody who has their bachelor degree in liberal arts shouldn't even dream of going to med school or being a lawyer. This line of reasoning is flawed. Some of the most successful people I've met in life have ended up doing things they never would have imagined.

Caligula 17y ago

Long 5am post alert broken into sections corresponding to the authors. I wish I read this 8 months ago so it could of prepared me for some of the misery to come. I initially thought it would be simple. Use some of the open source tools or commercial SDK's, then quickly move on to the important stuff. Did not turn out that way. In fact, speech recognition is a time killing whore, but it sure is interesting, sometimes at least. 1. Telephony & VoIP: I disagree with the author. Freeswitch comes with speech recognition built in and recently added uniMRCP so I think FS is definitely better not even taking into account how shady asterisk is. The prices he lists are also on the high side. You can get local DID's for half what he lists, probably further less in bulk. 2. Web Services: Agree with his comments on web services. Speech recognition is perfect for scaling onto the magical cloud. Dictation is more difficult because for very large vocabulary at least, your going to take up a system to process it and be lucky to get 1RT. 3. Embedded Disagree with this. Some decoders are made specificially for this. Well pocketsphinx is. It even used ARM ASM code to speed up calculations on embedded devices so you can get better results on the iphone for example. The developer for pocketsphinx for example recently made this fantastic demo for the N800 which I recall was similar to the iphone in power. http://www.youtube.com/watch?v=OEUeJb6Pwt4 http://www.youtube.com/watch?v=OEUeJb6Pwt4 And I am sure it can be tweaked to be even better. So much of speech recognition is tweaking. As he states correctly, Lumenvox is based on sphinx(sphinx2 I recall reading), just its very tweaked. Commercially available: Very funny, I agree with most. MS,AT&T,IBM suck at least for providing API's but their tech is very good. IBM for example released theirs as opensource but changed their mind and just let it die. Nuance is 'contact our salesperson' expensive. Lumenvox is the most affordable. Open Source: Minor nitpick, he should of included HTK with Julius. Acoustic models definitely have given me the most grief. I use sphinx4 and pocketsphinx and am very pleased. They are state of the art decoders. The acoustic model, or lack thereof is the reason why commercial engines are perceived as superior. If you have 50k you can spend get a LDC membership with tonnes of transcribed data. Slap it into the trainers format, BAM. Unfortunately I was not going to do this. I disliked the LDC for what I thought was gauging. Same prices for mega corporations as individuals. But after making my own model, and still in the neverending process of making my own, tweaking it, etc.., I appreciate the misery that is collecting and organizing transcribed data and appreciate the work they do even if I can't use it. Notice something wrong with your model, need to retrain it. Takes days with a quad core. In fact my new 8core beast of a server I ordered arrives next week, I wonder how my parents will take the noise, apparently servers are loud. Even with that it will take maybe half a day. And spotting errors is hard. I cant emphasize enough how boring it is to listen to hours on end of audio and see that it matches up with the text perfectly. In some cases, listening a bunch of times to make sure. Noticing issues with your model, having to go figure out why. Voxforge.org is great. They have ~50 hours of quality data, most at 16khz computer microphone but a good portion at 8khz telephone. You can always downsample. But for dictation you need much more. You dont need thousands of hours unless your doing dictation and if that extra few percent is worth it. You can get good results with low hundreds. There are other equally important factors like language models that he should of mentioned that could be equally as important as the acoustic model. How its important to have relevant, and lots of data to train them. The acoustic model is only one of many factors(as is the decoder for the matter). Perhaps because its that he did not focus on dictation that he left it out. Wrapping Up: FS better. At least try both, its trivial to set each up and follow a simple tutorial. You can still plug lumenvox into FS, although it will cost. But it would cost the same for asterisk. I agree that its difficult but I don't think that should stop you. Just be aware its a lot of work, some of it very boring and frustrating, but I am sure the same can be said for most things. Ok maybe not :)

danbmil99 17y ago

he starts out saying "stay the fuck away from this stuff" then goes on to talk lovingly of the tech. WTF? Where's the explanation of why it didn't work as a business? I think the OP is a bit too in love with the technology, that's probably why he got burnt.

mbrubeck 17y ago
And he said exactly that in his previous post: "So the number one reason my startup failed was: I was distracted by a cool and shiny feature that didn’t solve anyone’s problem." http://www.teabuzzed.com/2009/08/the-number-one-reason-my-startup-failed/ http://www.teabuzzed.com/2009/08/the-number-one-reason-my-st...

fjabre 17y ago

BTW just to clarify: by all means integrate speech rec into your solution if you feel you get a real value proposition by doing so. For my product it wasn't really needed and was more of a distraction than anything else. However I learned so much in the process I wanted to share this back with the community.