> 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

> 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.