pocketsphinx
Spoken-Keyword-Spotting
| pocketsphinx | Spoken-Keyword-Spotting | |
|---|---|---|
| 6 | 1 | |
| 3,745 | 80 | |
| 0.9% | - | |
| 7.4 | 0.0 | |
| about 1 month ago | over 1 year ago | |
| C | Python | |
| GNU General Public License v3.0 or later | MIT License |
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pocketsphinx
- [Discussion] Looking for an Open-Source Speech to Text model (english) that captures filler words, pauses and also records timestamps for each word.
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I Created A Web Speech API NPM Package Called SpeechKit
There are espeak-ng https://github.com/espeak-ng/espeak-ng and pocketsphinx https://github.com/cmusphinx/pocketsphinx which can be used locally without making external requests.
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"Why not just transcribe the audio?" I thought
And so I installed PocketSphinx, "one of Carnegie Mellon University's open source large vocabulary, speaker-independent continuous speech recognition engines."
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How to train large deep learning models as a startup
- https://github.com/cmusphinx/pocketsphinx
This avoids having to stream audio 24x7 to a cloud model which would be super expensive. This being said, I'm pretty sure what the Alexa does, for example, is send any positive wake word to a cloud model (that is bigger and more accurate) to verify the prediction of the local wake word detection model AFAIK.
- Speech recognition library for financial markets
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Speech recognition
PocketSphinx is generally regarded among voice assistant communities as a less reliable, but straight OOTB, alternative to a robust listener. It's a good solution when you want multiple hotwords (or just aren't in a position to train even one word.)
Spoken-Keyword-Spotting
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How to train large deep learning models as a startup
The search term you're looking for is "Keyword Spotting" - and that's what's implemented locally for ~embedded devices that sit and wait for something relevant to come along so that they know when to start sending data up to the mothership (or even turn on additional higher-power cores locally).
Here's an example repo that might be interesting (from initial impressions, though there are many more out there) : https://github.com/vineeths96/Spoken-Keyword-Spotting
What are some alternatives?
vosk - VOSK Speech Recognition Toolkit
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.
snowboy - Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy
svm-pytorch - Linear SVM with PyTorch
vosk-api - Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
determined - Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
localcroft - Bits for locally-served Mycroft instances
C_to_Python_translator - Using File I/O we were able to convert C code written in one text file to Python code in another text file with the application of multiple function that could identify and accordingly process specific key words and formats used in the C language.
xla - Enabling PyTorch on XLA Devices (e.g. Google TPU)
speech-kit - Simplifying the Speech Synthesis and Speech Recognition engines for Javascript. Listen for commands and perform callback actions, make the browser speak and transcribe your speech!
espeak-ng - eSpeak NG is an open source speech synthesizer that supports more than hundred languages and accents.