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  • 2010:Audio Genre Classification
    ...that this proposal has been merged into the Test/Train task: [[2010:Audio Classification (Train/Test) Tasks]]. Please go there for the full task proposal. ...X 2005, MIREX 2007, MIREX 2008 and MIREX 2009. However, there was no genre classification task in 2006.
    13 KB (2,010 words) - 22:47, 3 June 2010
  • 2005:Audio Genre Classification
    #REDIRECT [[2005:Audio Genre]]
    30 bytes (3 words) - 23:19, 10 May 2010
  • 2007:Audio Genre Classification
    A provisional specification of the genre classification task is detailed below. This proposal may be refined based on feedback from ...ex.php/Audio_Genre_Classification MIREX 2005]. However, there was no genre classification task in 2006.
    13 KB (1,934 words) - 16:57, 13 May 2010
  • 2007:Audio Genre Classification Results
    ...sted of 7000 30 second clips covering the following genres (700 tracks per genre): ...REX 2007 Audio Genre Classification Summary Results - Raw and Hierarchical Classification Accuracy Averaged Over Three Train/Test Folds===
    2 KB (311 words) - 11:47, 26 July 2010
  • 2008:Audio Genre Classification Results
    ...und information about this task set please refer to the [[2008:Audio Genre Classification]] page. ====MIREX 2008 Audio Genre Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds====
    9 KB (1,336 words) - 17:13, 23 July 2010
  • 2009:Audio Genre Classification (Latin Set) Results
    ...und information about this task set please refer to the [[2009:Audio Genre Classification]] page. More precisely, the Latin Music Database has 3,227 audio files from 10 Latin music genres:
    12 KB (1,676 words) - 16:20, 23 July 2010
  • 2009:Audio Genre Classification (Mixed Set) Results
    ...und information about this task set please refer to the [[2009:Audio Genre Classification]] page. ...lips in 22.05kHz mono WAV format drawn from 10 genres (700 clips from each genre). Genres:
    10 KB (1,475 words) - 16:02, 23 July 2010
  • 2005:Audio Genre Classification Results
    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 inf
    7 KB (877 words) - 11:41, 2 August 2010
  • 2013:Audio K-POP Genre Classification
    = 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
  • 2014:Audio K-POP Genre Classification
    = 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
  • 2015:Audio K-POP Genre Classification
    = 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
  • 2016:Audio K-POP Genre Classification
    = 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
  • 2018:Audio K-POP Genre Classification
    = 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
  • 2019:Audio K-POP Genre Classification
    = 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
  • 2020:Audio K-POP Genre Classification
    = 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

  • 2017:Main Page
    ** Audio Classification (Train/Test) Tasks <TC: IMIRSEL> ** Audio K-POP Genre Classification <TC: IMIRSEL>
    9 KB (1,363 words) - 12:20, 7 May 2018
  • 2010:MIREX HOME
    # Audio Classification (Train/Test) Tasks # Audio Music Similarity and Retrieval
    9 KB (1,296 words) - 05:32, 6 June 2011
  • 2010:Audio Genre Classification
    ...that this proposal has been merged into the Test/Train task: [[2010:Audio Classification (Train/Test) Tasks]]. Please go there for the full task proposal. ...X 2005, MIREX 2007, MIREX 2008 and MIREX 2009. However, there was no genre classification task in 2006.
    13 KB (2,010 words) - 22:47, 3 June 2010
  • 2005:Main Page
    ...represent the vast and multidisciplinary field of MIR, including symbolic, audio, and other subdisciplines. * [[2005:Audio Artist Identification]] - Deadline: 3 August 2005
    3 KB (375 words) - 22:50, 19 December 2011
  • 2005:Call For Participation
    * [[2005:Audio Artist Identification]] * [[2005:Audio Drum Detection]]
    3 KB (446 words) - 23:51, 10 May 2010
  • 2006:Main Page
    '''NOTE:''' Due to an evaluation error, the results of the [[2006:Audio Beat Tracking]] task have been updated as of 17 July 2007, and differ from * '''14 August 2006''': Deadline for [[2006:Audio Music Similarity and Retrieval]] and [[2006:Symbolic Melodic Similarity]] s
    7 KB (1,024 words) - 01:07, 15 December 2011
  • 2006:Audio Music Similarity and Retrieval
    Results are on [[2006:Audio Music Similarity and Retrieval Results]] page. ...o the lack of ground truth for music similarity, other evaluations such as genre and artist identification have been used as surrogates for music similarity
    19 KB (2,848 words) - 13:13, 13 May 2010
  • Audio Test/Train tasks
    ...sification tasks that follow this Train/Test process. For MIREX 2010, five classification sub-tasks are included: * Audio Artist Identification
    3 KB (327 words) - 14:12, 3 June 2010
  • 2007:Audio Artist Identification
    Note that audio artist identifcation algorithms have been evaluated at ISMIR 2004 and MIREX * [[2007:Audio Music Mood Classification]]
    8 KB (1,172 words) - 16:57, 13 May 2010
  • 2007:Audio Artist Similarity
    Note that audio artist similarity algorithms have been evaluated at [http://ismir2004.ismir * [[2007:Audio Music Mood Classification]]
    1 KB (171 words) - 16:57, 13 May 2010
  • 2007:Audio Classical Composer Identification
    =FINAL 2007 AUDIO CLASSICAL COMPOSER IDENTIFICATION EVALUATION SCENARIO OVERVIEW= ...is put here to clarify what will happen for this year's "beta" run of the Audio Classical Composer (ACC) ID task.
    5 KB (751 words) - 16:57, 13 May 2010
  • 2007:Audio Genre Classification
    A provisional specification of the genre classification task is detailed below. This proposal may be refined based on feedback from ...ex.php/Audio_Genre_Classification MIREX 2005]. However, there was no genre classification task in 2006.
    13 KB (1,934 words) - 16:57, 13 May 2010
  • 2007:Audio Genre Classification Results
    ...sted of 7000 30 second clips covering the following genres (700 tracks per genre): ...REX 2007 Audio Genre Classification Summary Results - Raw and Hierarchical Classification Accuracy Averaged Over Three Train/Test Folds===
    2 KB (311 words) - 11:47, 26 July 2010
  • 2007:Audio Music Mood Classification
    ...e to clarify what will happen for this year's "beta" run of the Audio Mood Classification (AMC) task. # We will operate the AMC task as a classic train-test classification task.
    27 KB (4,155 words) - 23:05, 19 December 2011
  • 2007:Audio Music Similarity and Retrieval
    A provisional specification of the Audio Music Similarity task is detailed below. This proposal may be refined based Note that audio music similarity and retrieval algorithms have been evaluated at MIREX 2006
    12 KB (1,800 words) - 16:57, 13 May 2010
  • 2007:MIREX2007 Results
    * [[2007:Audio_Artist_Identification_Results | Audio Artist Identification Results]] (READY) * [[2007:Audio_Classical_Composer_Identification_Results | Audio Classical Composer Identification Results ]] (READY)
    2 KB (276 words) - 01:12, 15 December 2011
  • 2007:Main Page
    * [[2007:Audio Artist Identification]] * [[2007:Audio Classical Composer Identification]] - [[2007:Audio Artist Identification]] subtask
    6 KB (748 words) - 22:56, 19 December 2011
  • 2005:MIREX2005 Results
    * [[2005:Audio_Artist_Identification_Results | Audio Artist Identification Results]] * [[2005:Audio_Drum_Detection_Results | Audio Drum Detection Results]]
    2 KB (197 words) - 00:05, 30 July 2010
  • 2008:Audio Genre Classification Results
    ...und information about this task set please refer to the [[2008:Audio Genre Classification]] page. ====MIREX 2008 Audio Genre Classification Summary Results - Raw Classification Accuracy Averaged Over Three Train/Test Folds====
    9 KB (1,336 words) - 17:13, 23 July 2010
  • 2008:Audio Music Mood Classification
    ...put here to clarify what will happen for this year's run of the Audio Mood Classification (AMC) task. # We will operate the AMC task as a classic train-test classification task.
    24 KB (3,695 words) - 14:08, 7 June 2010
  • 2008:MIREX2008 Results
    [https://www.music-ir.org/mirex/results/2008/tagPoster.pdf MIREX 2008 Classification tasks overall Results Poster (PDF)] is now available! * [[2008:Audio_Artist_Identification_Results | Audio Artist Identification Results]] (Done)
    3 KB (326 words) - 13:54, 7 June 2010
  • 2008:Main Page
    * [[2008:Audio Artist Identification]] * [[2008:Audio Genre Classification]]
    4 KB (490 words) - 16:53, 13 May 2010
  • 2009:Audio Tag Classification Tagatune Results
    ...ags (using the same statistical procedures as the the other MIREX 2009 tag classification tasks) and in the Tagatune game itself (the Tagatune metric). ...evaluation is very similar, if not identical, to the MIREX 2009 Audio Tag Classification tasks where two outputs are produced by each algorithm:
    29 KB (4,476 words) - 01:23, 15 December 2011
  • 2009:Audio Genre Classification (Latin Set) Results
    ...und information about this task set please refer to the [[2009:Audio Genre Classification]] page. More precisely, the Latin Music Database has 3,227 audio files from 10 Latin music genres:
    12 KB (1,676 words) - 16:20, 23 July 2010
  • 2009:MIREX2009 Results
    * [[2009:Audio_Classical_Composer_Identification_Results | Audio Classical Composer Identification Results ]] * [[2009:Audio_Genre_Classification_(Latin_Set)_Results | Audio Genre Classification (Latin Set) Results ]]
    2 KB (215 words) - 17:28, 6 July 2011
  • 2009:Audio Genre Classification (Mixed Set) Results
    ...und information about this task set please refer to the [[2009:Audio Genre Classification]] page. ...lips in 22.05kHz mono WAV format drawn from 10 genres (700 clips from each genre). Genres:
    10 KB (1,475 words) - 16:02, 23 July 2010
  • 2009:Main Page
    Pay attention to the wiki pages of tasks you are interested in. The Audio Music Similarity submission need to be submitted as close to the deadline a * [[2009:Audio Onset detection]]
    6 KB (923 words) - 16:52, 13 May 2010
  • 2009:Audio Music Mood Classification
    ...put here to clarify what will happen for this year's run of the Audio Mood Classification (AMC) task. # We will operate the AMC task as a classic train-test classification task.
    25 KB (3,811 words) - 23:32, 19 December 2011
  • 2009:Audio Music Mood Classification Results
    ...nformation about this task set please refer to the [[2009:Audio Music Mood Classification]] page. The data was created by Xiao Hu and consists of 600 files organized ...d J. Stephen Downie (2007)] '''Exploring mood metadata: Relationships with genre, artist and usage metadata''', In the 8th International Conference on Music
    12 KB (1,802 words) - 16:06, 23 July 2010
  • 2009:Scratch
    * [[2009:Audio_Genre_Classification_Results | Audio Genre Classification Results]] * Audio Tagging Tasks:
    2 KB (161 words) - 22:42, 13 May 2010
  • 2009:Audio Tag Classification (MajorMiner) Set Results
    ...ted to the other audio classification tasks, however, instead of one N-way classification per clip, this task requires N binary classifications per clip. These different outputs allow the algorithms to be evaluated both on tag 'classification' and tag 'ranking' (where the tags may be ranked for each track and tracks
    14 KB (1,882 words) - 16:33, 23 July 2010
  • 2010:Audio Music Similarity and Retrieval
    ...ng behind the approach taken in the evaluation. The intention of the Music Audio Search track is to evaluate music similarity searches (A music search engin The Audio Music Similarity and Retrieval task has been run in MIREX 2009, 2007, and 2
    14 KB (2,146 words) - 20:17, 18 June 2010
  • 2010:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,997 words) - 14:06, 7 June 2010
  • 2010:Audio Classification (Train/Test) Tasks
    ...sification tasks that follow this Train/Test process. For MIREX 2010, five classification sub-tasks are included: *Audio Artist Identification
    14 KB (1,932 words) - 11:15, 14 July 2010
  • Audio Train/Test Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2010, five classification sub-tasks are included:
    2 KB (282 words) - 13:09, 4 June 2010
  • Audio Classification
    * [[2005:Audio Artist Identification]] * [[2005:Audio Genre Classification]]
    421 bytes (36 words) - 04:53, 4 June 2010
  • 2010:Audio Music Mood Classification
    ...put here to clarify what will happen for this year's run of the Audio Mood Classification (AMC) task. # We will operate the AMC task as a classic train-test classification task.
    24 KB (3,662 words) - 23:34, 19 December 2011
  • 2009:Audio Tag Classification
    ...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 spec
    26 KB (3,980 words) - 23:36, 19 December 2011
  • 2009:SpecialTagatuneEvaluation
    ...evaluation is very similar, if not identical, to the MIREX 2008 Audio Tag Classification task. ...h indicates the absence of an instrument (e.g. no piano, no guitar) or the genre that the song does not belong to (e.g. not classical, not rock). Particip
    10 KB (1,727 words) - 14:07, 7 June 2010
  • 2010:MIREX2010 Results
    ...nois.edu/nema_out/4ffcb482-b83c-4ba6-bc42-9b538b31143c/results/evaluation/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; (DIY) ...6731c97a-240c-4d3d-8be9-90d715ea04e1/results/evaluation/ Audio Latin Genre Classification Results ]&nbsp;&nbsp; (DIY)
    4 KB (621 words) - 22:28, 23 October 2011
  • 2005:Audio Genre Classification Results
    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 inf
    7 KB (877 words) - 11:41, 2 August 2010
  • 2010:MIREX 2010 Poster List
    ...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 Test
    6 KB (843 words) - 04:25, 10 August 2010
  • 2011:MIREX Home
    # Audio Classification (Train/Test) Tasks # Audio Music Similarity and Retrieval
    8 KB (1,099 words) - 14:31, 1 October 2011
  • 2010:Runtime
    '''Task 4''' (MIREX 2010: Audio Train/Test: Genre Classification (Latin) - MIREX09 Dataset) ...assification task requiring participants to classify music audio tracks by Genre, where the genres are drawn from a set of Latin music genres collected in B
    10 KB (1,396 words) - 18:14, 26 October 2010
  • MIREX Impact Statements
    ...s view, I founded an annual evaluation campaign relating to my main focus (audio source separation), which has attracted more than 80 entrants in total and ...n eXchange (MIREX) initiative ..." in J. Serrà, E. Gómez and P. Herrera. Audio cover song identification and similarity: background, approaches, evaluatio
    5 KB (775 words) - 14:14, 22 May 2011
  • 2011:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,982 words) - 15:43, 8 July 2011
  • 2011:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2011, five classification sub-tasks are included:
    13 KB (1,875 words) - 15:48, 8 July 2011
  • 2011:MIREX2011 Results
    * [https://www.music-ir.org/nema_out/mirex2011/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; (DIY) ...usic-ir.org/nema_out/mirex2011/results/act/latin_report/ Audio Latin Genre Classification Results ]&nbsp;&nbsp; (DIY)
    4 KB (596 words) - 17:21, 18 May 2012
  • 2011:MIREX 2011 Poster List
    # 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
  • 2007:Discussion Points Euro MIREX Meeting
    ===Topic 1: First Task Proposal For MIREXDIYDEMO Prototype: Audio Cover Song?=== ...posed MIREXDIYDEMO framework for submission and evaluation. I believe that Audio Cover Song is a good choice because the the ground-truth is fixed (i.e., ei
    9 KB (1,385 words) - 01:47, 15 December 2011
  • 2008:Audio Tag Classification
    ...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 from
    22 KB (3,434 words) - 23:39, 19 December 2011
  • 2012:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2012, five classification sub-tasks are included:
    11 KB (1,608 words) - 16:39, 7 June 2012
  • 2012:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,970 words) - 16:30, 7 June 2012
  • 2012:MIREX Home
    ...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 o
    10 KB (1,554 words) - 05:31, 14 March 2013
  • 2012:MIREX2012 Results
    * [https://www.music-ir.org/nema_out/mirex2012/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; ...usic-ir.org/nema_out/mirex2012/results/act/latin_report/ Audio Latin Genre Classification Results ]&nbsp;&nbsp;
    5 KB (655 words) - 21:21, 5 October 2012
  • 2013:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2013, five classification sub-tasks are included:
    11 KB (1,608 words) - 11:33, 16 June 2013
  • 2013:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,970 words) - 11:16, 4 June 2013
  • 2013:Main Page
    * [[2013:Audio Classification (Train/Test) Tasks]], incorporating: ** Audio US Pop Genre Classification
    8 KB (1,225 words) - 22:35, 29 June 2014
  • 2013:Task Captains
    |[[2013:Audio Beat Tracking]] |[[2013:Audio Chord Estimation]]
    2 KB (294 words) - 16:14, 4 August 2013
  • 2013:Audio K-POP Genre Classification
    = 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
  • 2013:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,315 words) - 12:17, 19 January 2014
  • 2013:MIREX2013 Results
    * [https://www.music-ir.org/nema_out/mirex2013/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; ...usic-ir.org/nema_out/mirex2013/results/act/latin_report/ Audio Latin Genre Classification Results ]&nbsp;&nbsp;
    5 KB (688 words) - 23:23, 24 October 2014
  • 2014:Main Page
    ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval
    9 KB (1,330 words) - 14:32, 24 September 2014
  • 2014:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2014, five classification sub-tasks are included:
    11 KB (1,608 words) - 14:21, 7 January 2014
  • 2014:Audio K-POP Genre Classification
    = 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
  • 2014:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,315 words) - 14:27, 7 January 2014
  • 2014:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,970 words) - 14:32, 7 January 2014
  • 2014:Task Captains
    |[[2014:Audio Beat Tracking]] |[[2014:Audio Chord Estimation]]
    2 KB (300 words) - 21:27, 20 October 2014
  • 2014:MIREX2014 Results
    * [https://www.music-ir.org/nema_out/mirex2014/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; ...usic-ir.org/nema_out/mirex2014/results/act/latin_report/ Audio Latin Genre Classification Results ]&nbsp;&nbsp;
    6 KB (836 words) - 12:56, 31 October 2014
  • 2014:Timetable
    |[[2014:Audio Beat Tracking]] |[[2014:Audio Chord Estimation]]
    1 KB (137 words) - 13:54, 12 March 2014
  • 2015:Main Page
    ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval
    9 KB (1,308 words) - 23:02, 17 February 2016
  • 2015:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...sification tasks that follow this Train/Test process. For MIREX 2015, five classification sub-tasks are included:
    11 KB (1,608 words) - 11:39, 7 August 2015
  • 2015:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,315 words) - 21:17, 26 March 2015
  • 2015:Audio K-POP Genre Classification
    = 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
  • 2015:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    21 KB (2,970 words) - 21:23, 26 March 2015
  • 2015:MIREX2015 Results
    * [https://www.music-ir.org/nema_out/mirex2015/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp; ...usic-ir.org/nema_out/mirex2015/results/act/latin_report/ Audio Latin Genre Classification Results ]&nbsp;&nbsp;
    6 KB (750 words) - 10:20, 26 October 2015
  • 2016:Main Page
    ** Audio Classification (Train/Test) Tasks ** Audio Music Similarity and Retrieval
    9 KB (1,271 words) - 12:20, 7 May 2018
  • 2016:Audio Classification (Train/Test) Tasks
    = 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
  • 2016:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,315 words) - 15:06, 17 February 2016
  • 2016:Audio K-POP Genre Classification
    = 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
  • 2016:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    20 KB (2,950 words) - 15:14, 17 February 2016
  • 2017:MIREX2017 Results
    * [[2017:Audio Fingerprinting Results|Audio Fingerprinting Results]] ** [https://www.music-ir.org/nema_out/mirex2017/results/act/composer_report/ Audio Classical Composer Identification Results ]&nbsp;&nbsp;
    4 KB (517 words) - 11:20, 26 April 2018
  • 2018:Main Page
    ** [[2018:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including *** Audio US Pop Genre Classification
    9 KB (1,261 words) - 12:13, 22 August 2018
  • 2018:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...ssification tasks that follow this Train/Test process. For MIREX 2018, six classification sub-tasks are included:
    11 KB (1,643 words) - 10:31, 7 May 2018
  • 2018:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,314 words) - 10:37, 7 May 2018
  • 2018:Audio K-POP Genre Classification
    = 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
  • 2018:MIREX2018 Results
    * Audio Melody Extraction Results * [[2018:Audio Fingerprinting Results|Audio Fingerprinting Results]]
    4 KB (476 words) - 16:18, 14 October 2020
  • 2019:Main Page
    ** [[2019:Audio Fingerprinting]] <TC: Chung-Che Wang> ** [[2019:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
    8 KB (1,245 words) - 15:46, 27 January 2020
  • 2019:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...ssification tasks that follow this Train/Test process. For MIREX 2018, six classification sub-tasks are included:
    11 KB (1,643 words) - 17:00, 7 March 2019
  • 2019:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,314 words) - 17:04, 7 March 2019
  • 2019:Audio K-POP Genre Classification
    = 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
  • 2019:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    20 KB (2,950 words) - 17:17, 7 March 2019
  • 2019:MIREX2019 Results
    * Audio Melody Extraction Results * [[2019:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]] &nbsp;
    4 KB (502 words) - 16:30, 14 October 2020
  • 2020:Main Page
    ** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang> ** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
    8 KB (1,186 words) - 18:46, 31 August 2020
  • 2020:Audio Classification (Train/Test) Tasks
    = Audio Classification (Test/Train) tasks = ...ssification tasks that follow this Train/Test process. For MIREX 2019, six classification sub-tasks are included:
    11 KB (1,643 words) - 23:43, 1 June 2020
  • 2020:Audio K-POP Mood Classification
    = 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 annot
    9 KB (1,314 words) - 23:45, 1 June 2020
  • 2020:Audio K-POP Genre Classification
    = 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
  • 2020:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    20 KB (2,950 words) - 23:57, 1 June 2020
  • 2020:MIREX2020 Results
    * [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]] * Audio Melody Extraction Results
    3 KB (409 words) - 01:08, 15 October 2020
  • 2021:Audio Tag Classification
    ...ver, multiple tags may be applied to each example rather than single-label classification. Audio tag classification was first run at MIREX 2008 [[2008:Audio_Tag_Classification]] and as a spec
    20 KB (2,950 words) - 14:51, 10 September 2021
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