Reconocimiento de voz usando Deep Learning, mediante redes convolucionales proponemos un sistema de reconocimiento de voz mediante un clasificador de imágenes mediante el uso de espectrogramas

This repository is mainly about the classification of music genres of Kaggle music dataset in various forms of data preparation

Python program that converts an image file to audio

Application to remove background noise from audio files

Convert pixel data to a wav file

Audio Classification with CNN

Minimal realtime spectrogram application using Web Audio API.

Our goal is to push the general performance of music genre recognition forward and introduce a new method for pre-processing which allows for faster experimentation and model tuning in the future. We experimented with two different musical representations: mel-spectrograms and manually extracted features.

Concept checking

Brief sample of the development medium of a shrimp survival model in shrimp pools.

Music genre classification through the use of spectrograms. Final project for Artificial Neural Networks and Deep Learning.

Spectrogram Visualization

We will apply deep learning techniques for the classification of the free-spoken-digit-dataset, akin to an audio version of MNIST.

A C++ experiment in embedding images into wav file spectrographs.

语音降噪

An algorithm to find target frequencies in an audio signal

fast.ai's courses and software make it extremely easy to start working on difficult projects very quickly. This is just another example of that. This is a Bird Sound Classifying Deep Learning model, which takes in bird sounds, converts them into images (spectograms), and then classifies those images based on what type of bird call it is. The dat…

Simple analysis and implementation of a spectrogram for wav files. Signal processing course project.

The Project has various ideas and programs to help classify music tracks according to genres using ANN , CNN.and RNN with LSTM.