Yeah not intending to downplay what the author created, but the voice recognition and voice commands are kind of the key advertised feature of Alexa, so calling something without those an "Alexa knockoff" is a stretch at best.
Also agree. I get it if the author wanted a catchy title, because you want your work to be read, but the line between this and clickbait is a fine one.
Unless things have changed a lot in the past few months, they actually are pretty limited locally at this point. Certainly you can do them, but you can't them particularly well.
Mostly from playing a bit with Sphinx and loosely following the space. But as you say things are always changing.
I will note that different people have different definitions of "good" in this space. For example, I've used online services like otter.ai and, while they're useful for certain purposes, they're still much worse than a human for transcribing. They're certainly not worth my time to clean them up to publish an actual transcript.
but for something like Alexa which is designed to recognize specific commands it would be easy to design something with relatively good accuracy
I have not tried the other [otter.ai] service but even with speech to text on my iPhone, which to note is not running luckily [locally], it seems pretty accurate at transcribing what i say
^ the above was transcribed on an iPhone and the errors are bracketed.
While it doesn't offer what Alexa does, I'd like to point out that Mycroft would be easy to add to this project. I haven't really worked with it, but I did want to point it out for people who are coming into the comments looking for an actual open source Alexa competitor.
Based on this title style I built a google and gmail knockoff - using index cards, ink and paper and postage stamps. It doesn't spy on me - but also doesn't work at all like google or gmail!
Yeah, I was expecting to see a blog post about raspberry pi speech recognition. I was hoping it wasn't just another "look, Ma, I did speech recognition! (By sending everything to <cloud API>)" but I was prepared to be disappointed on that front because such posts are endemic these days. Turns out, it didn't engage with speech recognition at all, which was even more jarring.
Speaking of rpi offline speech recognition, is Jasper still the go-to? If you're willing to spring for one of the shiny new nvidia SBCs, is there an open source option that can take advantage of their power (with lower effort than "glue everything together manually with tensorflow")?
If this was to be called an "Alexa alternative", there should at least be Home Assistant running on that Raspberry Pi. Despite also not having voice recognition, it could then at least be able to, you know, DO something.
It's a knockoff, but doesn't include NLU or ASR capabilities so really it's a shitty tablet on a kickstand I could have purchased for roughly the same price with more features.
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[ 2.8 ms ] story [ 48.7 ms ] threadNor are they that hard to do with the right libraries
wav2letter can transcribe locally and well.
I will note that different people have different definitions of "good" in this space. For example, I've used online services like otter.ai and, while they're useful for certain purposes, they're still much worse than a human for transcribing. They're certainly not worth my time to clean them up to publish an actual transcript.
I have not tried the other [otter.ai] service but even with speech to text on my iPhone, which to note is not running luckily [locally], it seems pretty accurate at transcribing what i say
^ the above was transcribed on an iPhone and the errors are bracketed.
The "Alexa" knockoff has no voice recognition!
Based on this title style I built a google and gmail knockoff - using index cards, ink and paper and postage stamps. It doesn't spy on me - but also doesn't work at all like google or gmail!
Better title:
I built an LCD display that displays information?
Speaking of rpi offline speech recognition, is Jasper still the go-to? If you're willing to spring for one of the shiny new nvidia SBCs, is there an open source option that can take advantage of their power (with lower effort than "glue everything together manually with tensorflow")?