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What is the difference from a speech recognition API and [NLP libraries]( https://opennlp.apache.org/ )? This information was not easily found with a few google searches, so I figured others might have the same question.
As others here have pointed out, the value now for GOOG is in building the best training data-set in the business, as opposed to just racing to find the best algorithm.
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Like most machine-learning applications, the source code isn't the interesting part, the data is. Google started by training on millions of phrases from Google 411, and then they've been able to continue training anytime someone issues a voice command to an Android device. They have orders of magnitude more data than you could fit into a GitHub repository.
Couldn't you just download subtitles for old movies and train using those?
This is HUGE in my opinion. Prior to this, in order to get near state-of-the-art speech recognition in your system/application you either had to have/hire expertise to build your own or pay Nuance a significant amount of money to use theirs. Nuance has always been a "big bad" company in my mind. If I recall correctly, they've sued many of their smaller competitors out of existence and only do expensive enterprise dea…
Other "state-of-the-art" speech recognition solutions already exist. For example, Microsoft has been offering it through its Project Oxford service. https://www.projectoxford.ai/speech
Speech Intent Recognition
... the server returns structured information about the incoming speech so that apps can easily parse the intent of the speaker, and subsequently drive further action. Models trained by the Project Oxford LUIS service are used to generate the intent.
Do others offer something like this?
Has anyone tried adding OpenEars to their app, to prevent having to send things over the internet from e.g. a basement? Is it any good at recognizing basic speech?
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Couldn't you just download subtitles for old movies and train using those?
Doesn't even need to be old movies. Certain types of video content in the US is legally required to have subtitles(e.g. a lot of youtube content). You could programmatically download them and use that as your training set. And, since it is a transformative work, you can train your models even on copyrighted works freely.
This is HUGE in my opinion. Prior to this, in order to get near state-of-the-art speech recognition in your system/application you either had to have/hire expertise to build your own or pay Nuance a significant amount of money to use theirs. Nuance has always been a "big bad" company in my mind. If I recall correctly, they've sued many of their smaller competitors out of existence and only do expensive enterprise dea…
If it's anything like Googles other APIs, people will build applications on top of it, and then Google will decide to shut down the API with no notice. Fun to play with, but don't expect it to last...
Disclosure: I work on Compute Engine.
Will be interesting to compare with http://www.speechmatics.com
There's no hint of pricing that I could find on their page. Do you know about their pricing model?
Nice. But what I want is open-source speech recognition.