hadryan Goto Github PK

music-generation-using-rnn

The current technological advancements have transformed the way we not only produce, but listen and work with music. In this notebook, we will use Recurrent Neural Networks, to build a character-based model that generates jazz piano notes.

music-genre-categorization

music-genre-classification

Classifying English Music (.mp3) files using Music Information Retrieval (MIR), Digital/Audio Signal Processing (DIP) and Machine Learning (ML) Strategies

music-genre-classification-1

Music Genre Classification for 6 Genres with accuracy upto 85%

music-genre-classification-10

Music Genre Classification

music-genre-classification-11

Utilize deep learning models to determine song genres using raw audio.

music-genre-classification-12

A music genre classification project. Audio source: gtzanetakis, Million Song Dataset; ML Libraries: Keras, Tensorflow, Pytorch; NN Models: CNN, RNN.

music-genre-classification-13

Perform three types of feature extraction: STFT, MFCC and MelSpectrogram. Apply CNN/VGG with or without RNN architecture. Able to achieve 95% accuracy.

music-genre-classification-2

Recognizing the genre of music files using machine learning and deep learning models

music-genre-classification-3

Automatic Music Genre Classification with Machine Learning Techniques

music-genre-classification-4

Classification of audio 1,000 audio tracks into 10 musical categories using 2 methods. Conversion to a visual representation of the track and training a convolutional neural network, and extraction of key auditory features and training a linear neural network

music-genre-classification-5

Music genres is the taste, style and relax giving flow of a music. The genre of music refers to multiple types and categorization of music. The different types of famous music genre that we widely known are rock, jazz, reggae, classical, folk, blues, R & B, metal, dubstep, techno, country music, electro and pop. The key success of music in music industry is the genres of classified music that becomes a significant part of communicating music that provides bonding with relatively to human and masses of people. In contrast, the genre that falls under top-level style of rock are punk, indie, shoegaze, AOR and metal. They are basically subgenre of a music classification and it is important describing music to other people. In practical life, music is often used for multiple purposes due to physiological and social effects. Companies like Spotify, Soundcloud, Apple Music, Wynk & products like Shazam use music classification to provide their customers different flavour of music by recommending music they prefer to listen. we use python libraries such as Librosa and PyAudio library for audio processing in Python. We apply and use GTZAN dataset that is composed of 1000 audio tracks each 30-second-long representing 10 genres with 22050Hz mono audio file of 16bit in .au format for dataset. The functionality and working of music genre classification determine the help of Machine Learning algorithms. The algorithm such as KNN and artificial neural network (ANN) analyses and find out the similar similarity of genre features of music and classify it.

music-genre-classification-6

Music Genre Recognition App With Accuracy of 89%.

music-genre-classification-7

music-genre-classification-8

This project aims to model a classifier to classify songs into different genres using tensor flow library.

music-genre-classification-9

A Convolutional Neural Network written in Python with the goal of identifying music genres. This project was written for CSC 434 and follows Velerio Velardo's tutorial on the same topic.

music-genre-classification-and-prediction-system

This is a Machine Learning which classifies and predicts the music genre from songs of .wav format

music-genre-classification-and-recommendation

music-genre-classification-feature-extraction

Music genre classification: Feature extraction

music-genre-classification-ml

Audio Feature Based Music Genre Classification Using Machine Learning Models

music-genre-classification-recommendation

Music Genre Classification & Recommendation (MSBD5001)

music-genre-classification-with-audio-features

Analyze the audio features of songs to determine their music genre.

music-genre-classification-with-deep-learning

Using deep learning to predict the genre of a song.

music-genre-classification-with-python

music-genre-classifier

Implementing different machine learning models on input music data and finding the most efficient method.

music-genre-feature-extraction

music-genre-prediction

Machine Learning and NLP was used to predict a song's genre based off its audio features and lyrics respectively. Users can test the models with lyrics they paste in onto our website.

music-genre-prediction-and-recommendation-system

music-genre-recodnizer

music-genre-recognition

The purpose of this project is to analyse the given audio sample and classify it into one of the 10 music genres. To accomplish this task, we use spectrograms and extract features from them, and use these features to classify the audio sample into a genre. The features of the audio sample are used in building this model.