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Add user-suggested angry musical excerpts
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Yading Song <yading.song@eecs.qmul.ac.uk> |
| date |
Mon, 27 Apr 2015 19:56:32 +0100 |
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2d307bb5d034 |
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1 {\rtf1\ansi\ansicpg1252\cocoartf1265\cocoasubrtf210
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2 \cocoascreenfonts1{\fonttbl\f0\fswiss\fcharset0 Helvetica;}
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3 {\colortbl;\red255\green255\blue255;}
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4 \paperw11900\paperh16840\margl1440\margr1440\vieww10800\viewh8400\viewkind0
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5 \pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural
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6
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7 \f0\fs24 \cf0 \
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8 This is the emotion dataset used for ISMIR 2012 paper "Evaluation of Musical Features for Emotion Classification"\
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9 \
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10 It contains 3 parts,\
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11 1. The top tags returned by last.fm (four emotion classes: happy, sad, angry, and relax)\
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12 2. A list of songs labelled with the retrieved from part 1\
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13 3. The fetched song titles that we used in this paper (due to the copyright, we didn't upload preview files)\
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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. \
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15 \
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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\
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17 \
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18 Feel free to contact me if you have any questions. \
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19 \
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20 Queen Mary University of London\
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21 Centre for Digital Music\
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22 Yading Song\
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23 yading.song@eecs.qmul.ac.uk} |
