picovoice
Porcupine
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picovoice | Porcupine | |
---|---|---|
13 | 31 | |
497 | 3,412 | |
6.2% | 1.8% | |
8.9 | 9.1 | |
5 days ago | 8 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
picovoice
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Speech Recognition in Unity: Adding Voice Input
Download the Picovoice Unity package
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Speech Recognition using Arduino Nano 33
Picovoice Platform GitHub Repository
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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 STM32: Building hands-free voice experiences
git clone --recurse-submodules \ https://github.com/Picovoice/picovoice.git
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Day 20: On-device Voice Assistant with Flutter
You can use the demo code we open-sourced. It includes wake word and context files, so you can start with them.
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Day 7: Making Cool Raspberry Pi Projects even Cooler with Voice AI (2/4)
You can check out the GitHub repo to see more open-source demos
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Offline Voice Assistant on a Microcontroller with 192KB RAM
Although interestingly enough, the README for the linked repo (https://github.com/Picovoice/picovoice) states that "The SDK is licensed under Apache 2.0 and available on GitHub to encourage independent benchmarking and integration testing." While source isn't provided and only compiled binaries are provided, that should give you permission to flip some bits to skip a license check.
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Voice processing in Embedded Systems
Checkout https://github.com/Picovoice/picovoice I saw it on an article from before and it seemed easy to get started on.
- Voice Control App
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Clock app controlled with offline voice recognition (Tutorial + article in comments)
Check out an article I wrote about it and the source code
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?
What are some alternatives?
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
snowboy - Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy
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.
mycroft-precise - A lightweight, simple-to-use, RNN wake word listener
spokestack-python - Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
Caffe - Caffe: a fast open framework for deep learning.
rhino - On-device Speech-to-Intent engine powered by deep learning
cheetah - On-device streaming speech-to-text engine powered by deep learning
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
DiscordSpeechBot - A speech-to-text bot for discord with music commands and more using NodeJS. Ideally for controlling your Discord server using voice commands, can also be useful for hearing-impaired people.
Caffe2