Porcupine
CoreML-Models
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Porcupine | CoreML-Models | |
---|---|---|
31 | 2 | |
3,424 | 6,221 | |
2.1% | - | |
9.1 | 2.3 | |
7 days ago | 10 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Porcupine
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I made a ChatGPT virtual assistant that you can talk to
I call it DaVinci. DaVinci uses Picovoice (https://picovoice.ai/) solutions for wake word and voice activity detection and for converting speech to text, Amazon Polly to convert its responses into a natural sounding voice, and OpenAI’s GPT 3.5 to do the heavy lifting. It’s all contained in about 300 lines of Python code.
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Speech Recognition in Unity: Adding Voice Input
Download pre-trained models: "Porcupine" from Porcupine Wake Word and Video Player Context from Rhino Speech-to-Intent repositories - You can also train a custom models on Picovoice Console.
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Speech Recognition with SwiftUI
Below are some useful resources: Open-source code Picovoice Platform SDK Picovoice website
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Speech Recognition with Angular
Download the Porcupine model and turn the binary model into a base64 string.
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OK Google, Add Hotword Detection to Chrome
Download Porcupine (i.e. Deep Neural Network). Run the following to turn the binary model into a base64 string, from the project folder.
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Hotword Detection for MCUs
Porcupine SDK Porcupine SDK is on GitHub. Find libraries for supported MCUs on the Porcupine GitHub repository. Arduino libraries are available via a specialized package manager offered by Arduino.
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Day 12: Always Listening Voice Commands with React.js
Looking for more? Explore other languages on the Picovoice Console and check out for fully-working demos with Porcupine on GitHub.
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Day 6: Making Cool Raspberry Pi Projects even Cooler with Voice AI (1/4)
Don't forget to visit Porcupine's Wake Word's Github repository to see Python demos. If you want to do something similar to the video above, find the open-source codes here
- Voice Assistant app in Haskell
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What does "end-to-end" mean?
I sometimes see the term "end-to-end", and it always passes right by my ears as marketing jargon. For example, there was a recent post today that linked to this page: https://picovoice.ai/, and you'll find the statement "... end-to-end platform for adding voice to anything on your terms". I did a quick Google search and it seems like the term is used in many different contexts (e.g., encryption, enterprise software for product development, etc.), but to be honest, I'm just not getting it. Maybe someone can explain here within the realm of embedded software? Could you provide some examples as well?
CoreML-Models
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I made an app completely on SwiftUI dedicated to browsing vehicles for sale on eBay. It got rejected for being too basic, should I justify any more time on this?
Super far fetched idea on passing 4.2 with iOS specific functionality: there are CoreML models specifically capable of identifying car makes and models (linked in this repo), which could allow you to take/select a photo, and automatically identify/search the car based on the prediction. That being said, it will not take into account nearly as many details as you can manually specify in your app. Nice work!
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[MacOs/Node JS] Is there a simple hand tracking library that works in node.js?
Mac? Use the built in coreml; https://github.com/likedan/Awesome-CoreML-Models
What are some alternatives?
snowboy - Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy
Swift-AI - The Swift machine learning library.
mycroft-precise - A lightweight, simple-to-use, RNN wake word listener
Tensorflow-iOS
Caffe - Caffe: a fast open framework for deep learning.
Caffe2
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
CoreML-samples - Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
BrainCore - The iOS and OS X neural network framework
MLKit - A simple machine learning framework written in Swift 🤖