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- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,219 words) - 02:52, 31 July 2013
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,272 words) - 17:16, 17 September 2014
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,272 words) - 21:18, 26 March 2015
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,272 words) - 15:08, 17 February 2016
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,271 words) - 10:38, 7 May 2018
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,271 words) - 17:05, 7 March 2019
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,271 words) - 23:45, 1 June 2020
Page text matches
- ** Audio Classification (Train/Test) Tasks <TC: IMIRSEL> ** Audio K-POP Genre Classification <TC: IMIRSEL>9 KB (1,363 words) - 12:20, 7 May 2018
- ...ver, is that many tags can apply to the same clip, so instead of one N-way classification per clip, this task requires N binary classifications per clip. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec26 KB (3,980 words) - 23:36, 19 December 2011
- To classify polyphonic music audio (in PCM format) into genre categories. ...ical genre taxonomy, while the USPOP categories are at a single level. The audio sampling rates used were either 44.1 KHz or 22.05 KHz (mono). More data inf7 KB (877 words) - 11:41, 2 August 2010
- ...Music Tracking using Tempo-aware On-line Dynamic Time Warping" (Real-time Audio to Score Alignment (a.k.a Score Following)) # Pasi Saari and Olivier Lartillot: "SubEnsemble - Classification framework based on the Ensemble Approach and Feature Selection" (Train Test6 KB (843 words) - 04:25, 10 August 2010
- # Franz de Leon, Kirk Martinez: WAIS @ MIREX 2011 (AMS and Genre Classifacation Tasks) # Brian McFee and Gert Lanckriet: ''Audio similarity via metric learning'' (AMS)6 KB (850 words) - 10:24, 27 October 2011
- ...ver, is that many tags can apply to the same clip, so instead of one N-way classification per clip, this task requires N binary classifications per clip. A provisional specification of the tag classification task is detailed below. This proposal may be refined based on feedback from22 KB (3,434 words) - 23:39, 19 December 2011
- ...the lead on running the 2012 <b>Query by Singing/Humming (QBSH)</b> and <b>Audio Melody Extraction (AME) Tasks </b>. We do not foresee any special deviation ...he dataset are equipped with metadata (e.g., artist and title), as well as audio content analysis, semantic annotations, lyrics, etc. Because the data is o10 KB (1,554 words) - 05:31, 14 March 2013
- |[[2013:Audio Beat Tracking]] |[[2013:Audio Chord Estimation]]2 KB (294 words) - 16:14, 4 August 2013
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,219 words) - 02:52, 31 July 2013
- = K-POP Mood Classification = ...stern (or other cultural) music can be applied to K-POP music; 2)to see if classification models can be equally effective on predicting mood labels by American annot9 KB (1,315 words) - 12:17, 19 January 2014
- ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval9 KB (1,330 words) - 14:32, 24 September 2014
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,272 words) - 17:16, 17 September 2014
- = K-POP Mood Classification = ...stern (or other cultural) music can be applied to K-POP music; 2)to see if classification models can be equally effective on predicting mood labels by American annot9 KB (1,315 words) - 14:27, 7 January 2014
- |[[2014:Audio Beat Tracking]] |[[2014:Audio Chord Estimation]]2 KB (300 words) - 21:27, 20 October 2014
- |[[2014:Audio Beat Tracking]] |[[2014:Audio Chord Estimation]]1 KB (137 words) - 13:54, 12 March 2014
- ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval9 KB (1,308 words) - 23:02, 17 February 2016
- = K-POP Mood Classification = ...stern (or other cultural) music can be applied to K-POP music; 2)to see if classification models can be equally effective on predicting mood labels by American annot9 KB (1,315 words) - 21:17, 26 March 2015
- = K-POP Genre Classification = ...effective on predicting genre labels by American annotator and predicting genre labels by Korean annotator.8 KB (1,272 words) - 21:18, 26 March 2015
- ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval9 KB (1,271 words) - 12:20, 7 May 2018
- = Audio Classification (Test/Train) tasks = ...ssification tasks that follow this Train/Test process. For MIREX 2016, six classification sub-tasks are included:11 KB (1,643 words) - 15:04, 17 February 2016
