5 ms·

It was so confusing figuring out what this service is supposed to do. Had to look up the documentation. In summary, from what I can gather 1. It doesn’t do any

by npalli 13y ago

It was so confusing figuring out what this service is supposed to do. Had to look up the documentation. In summary, from what I can gather 1. It doesn’t do any speech recognition (speech -> text), so not sure why they put Siri in the title. It is also not clear how they can ‘hijack’ the text from Siri to do this analysis. The ASR engines they talk about (CMU, OpenEars) have pretty horrible accuracy (compared to Siri or google voice). 2. Looks like they do some form of text normalization/correction, again not clear how they do it. 3. The actual service they provide is a form of named entity recognition (confusing named intent which clashes with the android intent mechanism in their examples). 4. Also they let you define your own entities to match. You can train them using a drop –down menu. Not sure how you can train hundreds of examples using point and click. This different from alchemy (or many others) because this is open source(?) http://www.alchemyapi.com/products/features/entity-extraction/ http://www.alchemyapi.com/products/features/entity-extractio... Given this service was for developers with an interest in NLP, it would have been good if they didn’t hide behind a snow job title like “Siri as a service”.

ar7hur 13y ago
> 1. It doesn’t do any speech recognition (speech -> text), so not sure why they put Siri in the title. It is also not clear how they can ‘hijack’ the text from Siri to do this analysis. The ASR engines they talk about (CMU, OpenEars) have pretty horrible accuracy (compared to Siri or google voice). Currently most Wit users use Google or Nuance with great success. You can even use Android's offline speech rec. That being said, CMU and OpenEars work well, as long as you provide them with good language models (which you can't do if you hack a quick project). Our plan is for Wit to automatically generate the right language models from your instance configuration. > 2. Looks like they do some form of text normalization/correction, again not clear how they do it. 3. The actual service they provide is a form of named entity recognition (confusing named intent which clashes with the android intent mechanism in their examples). We abstract the full NLP stack for the developer. How we do it is not really what matters to our developers, as long as it works :) Actually we use a combination of many different NLP and machine learning techniques. > 4. Also they let you define your own entities to match. You can train them using a drop –down menu. Not sure how you can train hundreds of examples using point and click. You don't need to train hundreds of examples. Plus, our users are not NLP/ML experts and they prefer a graphical UI. But that's true it could be still more efficient, we have good features in the roadmap for that :) > This different from alchemy (or many others) because this is open source(?) http://www.alchemyapi.com/products/features/entity-extractio.. http://www.alchemyapi.com/products/features/entity-extractio.... Alchemy is great as a set of NLP tools, some of them quite academical, but it's not designed from scratch to solve the problem we're trying to solve: enable the masses of developers to easily add a natural language interface to their app.
- _sh 13y ago
  > How we do it is not really what matters to our developers, as long as it works :) How you do it is most certainly what matters to developers, as soon as it doesn't work as expected :)
  - ar7hur 13y ago
    Fair enough. Theory is when you know everything but nothing works. Practice is everything works but no one knows why. Here, theory and practice are combined: nothing works and no one knows why :)
aquark 13y ago
You could SiriProxy (https://github.com/plamoni/SiriProxy https://github.com/plamoni/SiriProxy) as input to this to handle to speech-to-text part I'm running this at home and it works great for adding custom actions to Siri
- X4 13y ago
  I was initially thinking that this is just a SaaS2SaaS Wrapper around Google/Apple Speech recognition. Hey, tbh. wouldn't that be a clever way to market? hehe, that reminded me to SiriProxy. But to give the authors their credit back, it's not what I guessed. It's much more a GUI around a complex toolset that would require you to dig deep into mudwater, bad docs etc. So, yes it makes life easier and sense to use this in your app. I have not evaluated the quality of their service yet, but it's a Startup, it's not going to stop improving (hopefully) :) (Google/Apple are essentially powered by "Nuance", but with different qualities of training-data.) More NLP/AI Startups and more colloboration on HN please! 2cents: I hope people don't sell to their first working protoype to the Google/Apple/Microsoft Empire, but try to get big on with friendly startup-colloboration and with the help of investors/angels.
  - jjwiseman 13y ago
    Google doesn't use Nuance.
    - X4 13y ago
      Oh, that's interesting. Do you have more information?
film42 13y ago
Maybe I'm out of line, but if you're planning on tearing into what's wrong with something, try to offer something positive as well. Your feedback was great and constructive, it's just not very nice. I'll be honest, HN has a tendency (myself included) to have a first natural reaction of "how can I criticize this?" But just because something isn't faster than enterprise, or not-as-scalable, or not made in your framework of choice doesn't mean it's worthless. I think this project is amazing. Great job and I can't wait to see this mature.

by npalli 13y ago

ar7hur 13y ago

> 1. It doesn’t do any speech recognition (speech -> text), so not sure why they put Siri in the title. It is also not clear how they can ‘hijack’ the text from Siri to do this analysis. The ASR engines they talk about (CMU, OpenEars) have pretty horrible accuracy (compared to Siri or google voice). Currently most Wit users use Google or Nuance with great success. You can even use Android's offline speech rec. That being said, CMU and OpenEars work well, as long as you provide them with good language models (which you can't do if you hack a quick project). Our plan is for Wit to automatically generate the right language models from your instance configuration. > 2. Looks like they do some form of text normalization/correction, again not clear how they do it. 3. The actual service they provide is a form of named entity recognition (confusing named intent which clashes with the android intent mechanism in their examples). We abstract the full NLP stack for the developer. How we do it is not really what matters to our developers, as long as it works :) Actually we use a combination of many different NLP and machine learning techniques. > 4. Also they let you define your own entities to match. You can train them using a drop –down menu. Not sure how you can train hundreds of examples using point and click. You don't need to train hundreds of examples. Plus, our users are not NLP/ML experts and they prefer a graphical UI. But that's true it could be still more efficient, we have good features in the roadmap for that :) > This different from alchemy (or many others) because this is open source(?) http://www.alchemyapi.com/products/features/entity-extractio.. http://www.alchemyapi.com/products/features/entity-extractio.... Alchemy is great as a set of NLP tools, some of them quite academical, but it's not designed from scratch to solve the problem we're trying to solve: enable the masses of developers to easily add a natural language interface to their app.

_sh 13y ago
> How we do it is not really what matters to our developers, as long as it works :) How you do it is most certainly what matters to developers, as soon as it doesn't work as expected :)
- ar7hur 13y ago
  Fair enough. Theory is when you know everything but nothing works. Practice is everything works but no one knows why. Here, theory and practice are combined: nothing works and no one knows why :)

aquark 13y ago

You could SiriProxy (https://github.com/plamoni/SiriProxy https://github.com/plamoni/SiriProxy) as input to this to handle to speech-to-text part I'm running this at home and it works great for adding custom actions to Siri

X4 13y ago
I was initially thinking that this is just a SaaS2SaaS Wrapper around Google/Apple Speech recognition. Hey, tbh. wouldn't that be a clever way to market? hehe, that reminded me to SiriProxy. But to give the authors their credit back, it's not what I guessed. It's much more a GUI around a complex toolset that would require you to dig deep into mudwater, bad docs etc. So, yes it makes life easier and sense to use this in your app. I have not evaluated the quality of their service yet, but it's a Startup, it's not going to stop improving (hopefully) :) (Google/Apple are essentially powered by "Nuance", but with different qualities of training-data.) More NLP/AI Startups and more colloboration on HN please! 2cents: I hope people don't sell to their first working protoype to the Google/Apple/Microsoft Empire, but try to get big on with friendly startup-colloboration and with the help of investors/angels.
- jjwiseman 13y ago
  Google doesn't use Nuance.
  - X4 13y ago
    Oh, that's interesting. Do you have more information?

film42 13y ago

Maybe I'm out of line, but if you're planning on tearing into what's wrong with something, try to offer something positive as well. Your feedback was great and constructive, it's just not very nice. I'll be honest, HN has a tendency (myself included) to have a first natural reaction of "how can I criticize this?" But just because something isn't faster than enterprise, or not-as-scalable, or not made in your framework of choice doesn't mean it's worthless. I think this project is amazing. Great job and I can't wait to see this mature.