Mercurial > hg > emotion-recognition
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part 3 - happy files
author | Yading Song <yading.song@eecs.qmul.ac.uk> |
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date | Fri, 27 Mar 2015 23:03:44 +0000 |
parents | 2fca2ff3bf81 |
children |
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{\rtf1\ansi\ansicpg1252\cocoartf1265\cocoasubrtf210 \cocoascreenfonts1{\fonttbl\f0\fswiss\fcharset0 Helvetica;} {\colortbl;\red255\green255\blue255;} \paperw11900\paperh16840\margl1440\margr1440\vieww10800\viewh8400\viewkind0 \pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural \f0\fs24 \cf0 \ This is the emotion dataset used for ISMIR 2012 paper "Evaluation of Musical Features for Emotion Classification"\ \ It contains 3 parts,\ 1. The top tags returned by last.fm (four emotion classes: happy, sad, angry, and relax)\ 2. A list of songs labelled with the retrieved from part 1\ 3. The fetched song titles that we used in this paper (due to the copyright, we didn't upload preview files)\ 4. The audio files were fetched from Last.fm and 7Digital. Due to the copyright issue, this data set is only for research purpose. \ \ Please cite \'93Y. Song, S. Dixon, M. Pearce. Evaluation of musical features for emotion classification. In 13th International Society for Music Information Retrieval Conference (ISMIR), 2012.\'94\ \ Feel free to contact me if you have any questions. \ \ Queen Mary University of London\ Centre for Digital Music\ Yading Song\ yading.song@eecs.qmul.ac.uk}