공개 한국어 감성 검색 엔진 - 2017 제 11회 공개SW개발자대회 결선작

🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis

Generate vector embeddings for music

Categorize audio files by genre effortlessly. Use Dockerized environment and API to classify music genres.

beets plugin to auto-detect the genre for each item within your music library

Genre Classification Model Based on VGGish

This is Content based music recommendation system. I have used both audio features and lyrics (text based) features for recommending most similar songs to a given query song.

A Machine Learning project of estimating pitch of human vocal from songs by vocal separation

.wav files, training dataset (MFCC), and graph plots (FFTs, MFCCs, Waveforms) from Latin America, Asia, MiddleEast, and Africa

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

Dockerized benchmark model & API for classifying music by genre based on TensorFlow and Essentia

Models for music genre recognition

A two-class music genre classfier based on CNN (Convolutional Neural Network)

Automatic music genre classification using Multi-layer Perceptron (MLP)

Personality based Recommendation System

Music Loops Genre Classifier CNN

Using Deep Learning to Categorize Music through Spectrogram Analysis

Created as part of Audio and Music processing lab assignment. Extracts and analyses features from an audio collection, and creates playlists based on various descriptors. Can create playlists based on music similarity too.