Mercurial > hg > emotion-recognition

comparison readme.rtf @ 9:2d307bb5d034

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
part 3 - happy files
author Yading Song <yading.song@eecs.qmul.ac.uk>
date Fri, 27 Mar 2015 23:03:44 +0000
parents 2fca2ff3bf81
children
comparison
equal deleted inserted replaced
8:a690d5f1de40 9:2d307bb5d034
11 1. The top tags returned by last.fm (four emotion classes: happy, sad, angry, and relax)\ 11 1. The top tags returned by last.fm (four emotion classes: happy, sad, angry, and relax)\
12 2. A list of songs labelled with the retrieved from part 1\ 12 2. A list of songs labelled with the retrieved from part 1\
13 3. The fetched song titles that we used in this paper (due to the copyright, we didn't upload preview files)\ 13 3. The fetched song titles that we used in this paper (due to the copyright, we didn't upload preview files)\
14 4. The audio files were fetched from Last.fm and 7Digital. Due to the copyright issue, this data set is only for research purpose. \ 14 4. The audio files were fetched from Last.fm and 7Digital. Due to the copyright issue, this data set is only for research purpose. \
15 \ 15 \
16 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\
17 \
16 Feel free to contact me if you have any questions. \ 18 Feel free to contact me if you have any questions. \
17 \ 19 \
18 Queen Mary University of London\ 20 Queen Mary University of London\
19 Centre for Digital Music\ 21 Centre for Digital Music\
20 Yading Song\ 22 Yading Song\