Popular GitHub Repositories for Spectrograms

A neural network framework for researchers studying acoustic communication

Music genre classification model using CRNN

The details that matter: Frequency resolution of spectrograms in acoustic scene classification - paper replication data

Music genre classification using Convolutional Neural Networks on Spectrograms in PyTorch

Generating sound spectrograms using short-time Fourier transform that can be used for purposes such as sound classification by machine learning algorithms.

Deep learning using CNN for Mandarin Chinese tone classification

NTU RGB+D Dataset Action Recognition with GNNs and CNNs

Phoneme prediction from speech mel-spectrograms using RNN.

Text-to-Speech Synthesis by Generating Spectrograms using Generative Adversarial Network

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.

CNN, RNN and CRNN classification music by genre, with pre-processing into mel-spectrograms as pictures

A convolutional neural network which classifies music genres based on spectrograms.

Mood classification using spectrograms of sound

TinyML project. This system monitors your room or surrounding with an onboard microphone of Arduino nano BLE sense. Still Under Developement

Transfering many audios to spectrograms and finally to a torch martrix in order to prepare for machine learning.

Employing Adversarial Machine Learning and Computer Audition for Smartphone-Based Real-Time Arrhythmia Classification in Heart Sounds

Interactive app for pre-annotation of spectrogram images aided by deep-leaning based clustering

Audio visualization tool for generating detailed spectrograms from FLAC files, featuring customizable parameters and zoom functionality for precise audio analysis

NeuroTalk can demonstrate that EEG contain the properties needed to generate mel-spectrograms, and show that EEG can generate speech

This project makes spectrograms of data. Then, it uses an Image Classifier to train and classify those different spectrograms.