There are 2 repositories under stft topic.
Pyroomacoustics is a package for audio signal processing for indoor applications. It was developed as a fast prototyping platform for beamforming algorithms in indoor scenarios.
Audio processing by using pytorch 1D convolution network
Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python
YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.
Real time monaural source separation base on fully convolutional neural network operates on Time-frequency domain.
Audio Fingerprinting & Retrieval for .NET
STFT based real-time pitch and timbre shifting in C++ and Python
Simple demo of filtering signal with an LPF and plotting its Short-Time Fourier Transform (STFT) and Laplace transform, in Python.
C library for audio noise reduction and other spectral effects
Zafar's Audio Functions in Python for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
Zafar's Audio Functions in Matlab for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
Time stretching audio without changing pitch
Visualization of Audio Spectrogram with Short-Time Fourier Transform (STFT)
Noise-level estimation using minima controlled recursive averaging approach and denoising using Stein's unbiased risk estimates in STFT domain.
Doppler radar signal processing tested with HB100 and RCWL0516 radar modules
A simple tutorial of wavelet, STFT and FFT
Speech Denoising using RNNs in Tensorflow
CRED: A deep residual network of convolutional and recurrent units for earthquake signal detection
Official JUCE plugin for stftPitchShift
This repository contains the trained deep learning models for the detection and prediction of Epileptic seizures.
MATLAB + Python implementations of real-time median-filtering Harmonic-Percussive Source Separation
A Python implementation of STFT and MFCC audio features from scratch
Short-time Fourier transform (STFT) for JAX
Perform three types of feature extraction: STFT, MFCC and MelSpectrogram. Apply CNN/VGG with or without RNN architecture. Able to achieve 95% accuracy.
Spectral RNNs with adaptive window learning in TensorFlow, ICANN 2020.