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• 2010:Audio Classification (Train/Test) Tasks
  ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2010, f *Audio Artist Identification
  14 KB (1,932 words) - 11:15, 14 July 2010
• 2010:Audio Music Mood Classification
  ...section is put here to clarify what will happen for this year's run of the Audio Mood Classification (AMC) task. # Audio files: 30 sec., 22kHz, mono, 16 bit
  24 KB (3,662 words) - 23:34, 19 December 2011
• 2011:Audio Classification (Train/Test) Tasks
  = Audio Classification (Test/Train) tasks = ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2011, f
  13 KB (1,875 words) - 15:48, 8 July 2011
• 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
• 2015:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,271 words) - 02:40, 12 August 2015
• 2015:Music/Speech Classification and Detection
  The need for music-speech classification is evident in many audio processing tasks which relate to real-life materials such as archives of fi ...ication is here defined as the binary problem of classifying pre-segmented audio data to the speech or music class. We impose the restriction that a segment
  10 KB (1,550 words) - 23:01, 17 February 2016
• 2016:Audio Classification (Train/Test) Tasks
  = Audio Classification (Test/Train) tasks = ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2016, s
  11 KB (1,643 words) - 15:04, 17 February 2016
• 2016:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,265 words) - 22:37, 17 February 2016
• 2018:Audio Classification (Train/Test) Tasks
  = Audio Classification (Test/Train) tasks = ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2018, s
  11 KB (1,643 words) - 10:31, 7 May 2018
• 2018:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,265 words) - 10:52, 7 May 2018
• 2018:Music/Speech Classification and Detection
  The need for music-speech classification is evident in many audio processing tasks which relate to real-life materials such as archives of fi ...ication is here defined as the binary problem of classifying pre-segmented audio data to the speech or music class. We impose the restriction that a segment
  10 KB (1,548 words) - 10:54, 7 May 2018
• 2019:Audio Classification (Train/Test) Tasks
  = Audio Classification (Test/Train) tasks = ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2018, s
  11 KB (1,643 words) - 17:00, 7 March 2019
• 2019:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,265 words) - 17:15, 7 March 2019
• 2020:Audio Classification (Train/Test) Tasks
  = Audio Classification (Test/Train) tasks = ...unseen data. Therefore, we propose this "meta" task which includes various audio classification tasks that follow this Train/Test process. For MIREX 2019, s
  11 KB (1,643 words) - 23:43, 1 June 2020
• 2020:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,265 words) - 23:54, 1 June 2020
• 2021:Set List Identification
  ...he set list, and start/end time of each song. In this task, we collect the audio of live concerts and studio songs, applying music information retrieval tec ...s only''', however the ultimate goal is granted a full-length live concert audio and studio song database, we still can find out the set list and the start/
  8 KB (1,265 words) - 15:02, 10 September 2021

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