Analyze spectrograms created by rtl_power

A foobar2000 component that displays a spectrum analyzer.

Javascript port of the CCWT library (Complex continuous wavelet transformation)

iOS Microphone Stethoscope to Measure Heart Rate using AudioKit and Custom FFT

Web Audio high quality real-time spectogram from biquad bandpass filters

deep_video_extraction is a powerful repository designed to extract deep feature representations from video inputs using pre-trained models. With support for both visual and aural features from videos. Additionally, you can process audio separately by converting it into spectrograms.

A command line tool that paints images (or text) on audio spectograms

🌎 This repository contains unsupervised analysis of seismic data using Kmeans and Deep Embedded Clustering to identify different types of signals recorded in Seismograph 🕸️

Three in one. capture audio with mobile mic and then play, play songs from internal download directly, displaying spectogram (frequency) of an audio in Flutter.

Web Audio high quality spectogram from biquad bandpass filters

Southern African Bird Call Audio Identification Challenge

A Node-RED node for running an impulse created by the Edge Impulse development platform.

Building a speaker identification & verification pipeline for Vietnamese voices 😪

Current research project at CSU, Chico in collaboration with the Cornell Elephant Listening Project. Developing an Elephant infrasound detector.

Bronze medal solution for the kaggle competition HMS-Harmful Brain Activity Classification

A simple FFT-based tuner and spectogram

Snippets from learning tensorflow for audio data and models.

Introduction to Digital Signal Processing for Machine Learning

Audio classification can be performed by converting audio streams into spectrograms, which provide visual representations of spectrums of frequencies as they vary over time, and classifying the spectrograms using convolutional neural networks (CNNs).