verrannt/snn_speechrec

Convolutional Spiking Neural Network to recognize speech utterances using Spike-Timing-Dependent Plasticity

29
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Experimental

This project helps researchers and academics working with speech signals to explore an unsupervised approach to speech recognition. It takes raw speech recordings, processes them into features, and outputs classified speech utterances without needing labeled training data. This is ideal for those researching or applying advanced neural network architectures to audio processing.

No commits in the last 6 months.

Use this if you are a researcher or academic interested in experimenting with unsupervised speech recognition techniques, specifically those involving spiking neural networks and spike-timing-dependent plasticity.

Not ideal if you need a production-ready speech recognition system or a solution that offers the highest classification accuracy on complex, real-world datasets.

speech-recognition neuroscience-inspired-AI unsupervised-learning audio-processing academic-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 8 / 25

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Stars

9

Forks

1

Language

Python

License

GPL-3.0

Last pushed

Mar 09, 2021

Commits (30d)

0

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