GUI for a Vocal Remover that uses Deep Neural Networks.

Vocal Remover using Deep Neural Networks

Audio processing by using pytorch 1D convolution network

Real-time audio visualizations (spectrum, spectrogram, etc.)

kapre: Keras Audio Preprocessors

UrbanSound classification using Convolutional Recurrent Networks in PyTorch

.NET library for creating spectrograms (visual representations of frequency spectrum over time)

Predicting depression from acoustic features of speech using a Convolutional Neural Network.

Turn an image into sound whose spectrogram looks like the image.

The BEST music separation model with help of A.I. ... to my ears ! 👂👂

Frequency domain estimation and functional and directed connectivity analysis tools for electrophysiological data

🔥 Imagine ShaderToy, on a Manim-like architecture. That's ShaderFlow. Music visualizer, piano roll, shader platform. Fastest rendering times in the west

API for a Vocal Remover that uses Deep Neural Networks.

Final Year Project for Speech Separation

A simple audio feature extraction library

Recommending Music using a Convolutional Neural Network.

SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition

Source code complementing our paper for acoustic event classification using convolutional neural networks.

Music genre classification from audio spectrograms using deep learning

A Python library for computing the Mel-Cepstral Distance (Mel-Cepstral Distortion, MCD) between two inputs. This implementation is based on the method proposed by Robert F. Kubichek in "Mel-Cepstral Distance Measure for Objective Speech Quality Assessment".