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[//]: # (title: Build your customizable voice assistant with Platypush)
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[//]: # (description: Use the available integrations to build a voice assistant with a simple microphone)
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[//]: # (image: /img/voice-assistant-1.png)
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[//]: # (published: 2019-09-05)
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My dream of a piece of software that you could simply talk to and get things done started more than 10 years ago, when I
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was still a young M.Sc student who imagined getting common tasks done on my computer through the same kind of natural
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interaction you see between Dave and [HAL 9000](https://en.wikipedia.org/wiki/HAL_9000) in
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[2001: A Space Odyssey](https://en.wikipedia.org/wiki/2001:_A_Space_Odyssey_(film)). Together with a friend I developed
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[Voxifera](https://github.com/BlackLight/Voxifera) way back in 2008. Although the software worked well enough for basic
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tasks, as long as it was always me to provide the voice commands and as long as the list of custom voice commands was
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below 10 items, Google and Amazon in the latest years have gone way beyond what an M.Sc student alone could do with
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fast-Fourier transforms and Markov models.
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When years later I started building [Platypush](https://git.platypush.tech/platypush/platypush), I still dreamed of the
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same voice interface, leveraging the new technologies, while not being caged by the interactions natively provided by
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those commercial assistants. My goal was still to talk to my assistant and get it to do whatever I wanted to, regardless
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of the skills/integrations supported by the product, regardless of whichever answer its AI was intended to provide for
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that phrase. And, most of all, my goal was to have all the business logic of the actions to run on my own device(s), not
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on someone else’s cloud. I feel like by now that goal has been mostly accomplished (assistant technology with 100%
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flexibility when it comes to phrase patterns and custom actions), and today I’d like to show you how to set up your own
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Google Assistant on steroids as well with a Raspberry Pi, microphone and platypush. I’ll also show how to run your
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custom hotword detection models through the [Snowboy](https://snowboy.kitt.ai/) integration, for those who wish greater flexibility when it comes to
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how to summon your digital butler besides the boring “Ok Google” formula, or those who aren’t that happy with the idea
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of having Google to constantly listen to everything that is said in the room. For those who are unfamiliar with
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platypush, I suggest
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reading [my previous article](https://blog.platypush.tech/article/Ultimate-self-hosted-automation-with-Platypush) on
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what it is, what it can do, why I built it and how to get started with it.
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## Context and expectations
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First, a bit of context around the current state of the assistant integration (and the state of the available assistant APIs/SDKs in general).
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My initial goal was to have a voice assistant that could:
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1. Continuously listen through an audio device for a specific audio pattern or phrase and process the subsequent voice
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requests.
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2. Support multiple models for the hotword, so that multiple phrases could be used to trigger a request process, and
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optionally one could even associate a different assistant language to each hotword.
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3. Support conversation start/end actions even without hotword detection — something like “start listening when I press
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a button or when I get close to a distance sensor”.
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4. Provide the possibility to configure a list of custom phrases or patterns (ideally
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through [regular expressions](https://en.wikipedia.org/wiki/Regular_expression)) that, when matched, would run a
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custom pre-configured task or list of tasks on the executing device, or on any device connected through it.
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5. If a phrase doesn’t match any of those pre-configured patterns, then the assistant would go on and process the
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request in the default way (e.g. rely on Google’s “how’s the weather?” or “what’s on my calendar?” standard response).
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Basically, I needed an assistant SDK or API that could be easily wrapped into a library or tiny module, a module that could listen for hotwords, start/stop conversations programmatically, and return the detected phrase directly back to my business logic if any speech was recognized.
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I eventually decided to develop the integration with the Google Assistant and ignore Alexa because:
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- Alexa’s original [sample app](https://github.com/alexa/alexa-avs-sample-app.git) for developers was a relatively heavy
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piece of software that relied on a Java backend and a Node.js web service.
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- In the meantime Amazon has pulled the plug off that original project.
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- The sample app has been replaced by the [Amazon AVS (Alexa Voice Service)](https://github.com/alexa/avs-device-sdk),
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which is a C++ service mostly aimed to commercial applications and doesn’t provide a decent quickstart for custom
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Python integrations.
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- There are [few Python examples for the Alexa SDK](https://developer.amazon.com/en-US/alexa/alexa-skills-kit/alexa-skill-python-tutorial#sample-python-projects),
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but they focus on how to develop a skill. I’m not interested in building a skill that runs on Amazon’s servers — I’m
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interested in detecting hotwords and raw speech on any device, and the SDK should let me do whatever I want with that.
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<header>
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<a href="/">
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<div class="icon"></div>
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<div class="title">Platypush blog</div>
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<div class="title">PlatyBlog</div>
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</a>
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</header>
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<header>
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<a href="/">
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<div class="icon"></div>
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<div class="title">Platypush blog</div>
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<div class="title">PlatyBlog</div>
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</a>
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</header>
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