This is a submission for the AssemblyAI Challenge : Sophisticated Speech-to-Text and No More Monkey Business.
What I Built
I developed ...
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Nice work Rafael!!
Thanks! 😎
Wow, nice.
good job bro
Incredible!
@milewski This is very creative. Fantastic work. Love it.
Thanks! ✨
wow , as a beginner as i am , your project is awesome , how did you come up with such idea?
When I saw the sponsor's name, "AssemblyAI," it immediately made me think of embedded hardware... Assembly -> Low-Level -> Hardware. So, I decided to use some modules I had on hand and quickly brainstorm ways to make the most of it..
WOW you did such amazing work , if i wanna learn those IOT , which language should i start with?
I would say there are two ways:
You can go with C, your learning path will be easier, and you would benefit from tons of libraries for every module you can buy.
Or you can go with Rust. It’s definitely going to be a much harder journey, but in my opinion, it will be a much better deal for your future.
And in terms of platforms, there are three major ones: Arduino, STM32, and ESP32. Arduino might be the most popular, but its boards are expensive and have very low specs compared to ESP32, which is cheaper and, in most cases, offers much better hardware for the price.
I have a repository on GitHub where I documented my journey while learning this stuff. It might be helpful for you to take a look and see how much you understand or can follow by reading the code, so you can get an idea of how easy or hard it may be..
github.com/milewski/sensors-esp
Thanks a lot, what about using python?
It is possible to use Python, search for MicroPython... However, keep in mind that these devices have very limited memory. Using a language like Python, which is interpreted and includes a garbage collector, will consume most of the available memory, leaving very little for your application. The best approach is to use compiled languages with no runtime overhead, such as C or Rust.
To give you an idea of the challenges you might face (which are often unnoticed on conventional computers), I was unable to use the Get Transcription API because it returned a massive JSON response. This exceeded the memory available in my stack, and I only discovered the issue near the end of the project. As a result, I had to pivot my approach and use the Streaming API instead.
Okay that's great answer , thanks man
Do you really have any challenge community like dev community that I can participate by building websites and showcase them?
Muito bom! Parabéns