MusicMood: Predicting the mood of music from song lyrics using machine learning

11/01/2016
by   Sebastian Raschka, et al.
0

Sentiment prediction of contemporary music can have a wide-range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers, respectively. In this project, music recommendation system built upon on a naive Bayes classifier, trained to predict the sentiment of songs based on song lyrics alone. The experimental results show that music corresponding to a happy mood can be detected with high precision based on text features obtained from song lyrics.

READ FULL TEXT

page 2

page 5

page 6

research
03/09/2021

Learning to Generate Music With Sentiment

Deep Learning models have shown very promising results in automatically ...
research
12/03/2015

Predicting the top and bottom ranks of billboard songs using Machine Learning

The music industry is a 130 billion industry. Predicting whether a song ...
research
11/04/2019

Examining UK drill music through sentiment trajectory analysis

This paper presents how techniques from natural language processing can ...
research
09/04/2017

Musical NeuroPicks: a consumer-grade BCI for on-demand music streaming services

We investigated the possibility of using a machine-learning scheme in co...
research
03/13/2022

Bi-Sampling Approach to Classify Music Mood leveraging Raga-Rasa Association in Indian Classical Music

The impact of Music on the mood or emotion of the listener is a well-res...
research
09/17/2017

A Categorical Approach for Recognizing Emotional Effects of Music

Recently, digital music libraries have been developed and can be plainly...
research
04/09/2020

Violent music vs violence and music: Drill rap and violent crime in London

The current policy of removing drill music videos from social media plat...

Please sign up or login with your details

Forgot password? Click here to reset