snips-nlu-rs
Porcupine
snips-nlu-rs | Porcupine | |
---|---|---|
2 | 31 | |
337 | 3,496 | |
0.0% | 2.5% | |
10.0 | 9.0 | |
over 1 year ago | 14 days ago | |
Rust | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
snips-nlu-rs
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Ask HN: Offline, Embeddable Speech Recognition?
I am in shop for a speech recon library that works offline and can fit on a phone (Android).
I used to use Snips AI (https://snips.ai/), which worked well until it was acquired by Sonos. Now the portal is down and I can't modify the model anymore.
Looking for something ideally written in C or that can target C for portability. Free/libre and copyleft preferable to avoid the acquisition trap again.
Tapping into the vast pools of knowledge of HN; could you please suggest alternatives, preferably ones you have experience with?
Thank you.
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Getting long build times because of build script in dependency. Any work arounds?
Hey guys, I'm trying to write something that parses intents. I came across this: snips-nlu.
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?
rustling-ontology - Ontology for rustling
snowboy - Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
mycroft-precise - A lightweight, simple-to-use, RNN wake word listener
onnxruntime-rs - Rust wrapper for Microsoft's ONNX Runtime (version 1.8)
Caffe - Caffe: a fast open framework for deep learning.
SpeechLoop - Many ASRs under one roof. With Benchmarking... answering the question. What is the best ASR for my dataset?
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.
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Caffe2
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
whisper.cpp - Port of OpenAI's Whisper model in C/C++