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deconstructing_sample-based_electronic_dance_music [2015/10/25 10:19]
jonathan
deconstructing_sample-based_electronic_dance_music [2015/10/25 11:15] (current)
jonathan
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 | **Authors **| Patricio López-Serrano,​ Hendrik Schreiber, Jonathan Driedger, Richard Vogl, Sebastian Böck| | **Authors **| Patricio López-Serrano,​ Hendrik Schreiber, Jonathan Driedger, Richard Vogl, Sebastian Böck|
-| **eMail** | {patricio.lopez.serrano,​jonathan.driedger}@audiolabs-erlangen.de,​hs@tagtraum.com|+| **eMail** | [[patricio.lopez.serrano@audiolabs-erlangen.de]],[[jonathan.driedger@audiolabs-erlangen.de]],[[hs@tagtraum.com]],​[[richard.vogl@jku.at]],​[[sebastian.boeck@jku.at]]|
  
-EDM (Electronic Dance Music) is often constructed from //samples// or //loops//, stacked on top of each other. A common ​pattern ​of EDM artists ​is to start a song with a single loop. While the song builds up, more and more loops are added.+EDM (Electronic Dance Music) is often constructed from //samples// or //loops//, stacked on top of each other. A common ​workflow ​of EDM producers ​is to start a song with a single loop. While the song builds up, more and more loops are added.
  
 {{ :​step1.jpg?​nolink&​400 |}} {{ :​step1.jpg?​nolink&​400 |}}
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 {{ :​Moby_Porcelain_FullSong.mp3 |}} {{ :​Moby_Porcelain_FullSong.mp3 |}}
  
-The goal of our hack was the following: Given an EDM song that was build up in the above described ​way, we want to **break it into all the separate loops that were used to create it**. To this end, we came up with an iterative strategy.+The goal of our hack was the following: Given an EDM song that was built in the way described above, we want to **break it into all the separate loops that were used to create it**. To this end, we came up with an iterative strategy.
  
 ===== Step 1: Identifying Isolated Loops ===== ===== Step 1: Identifying Isolated Loops =====
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 {{ :​Moby_Porcelain_Iteration1_Loop.mp3 |}} {{ :​Moby_Porcelain_Iteration1_Loop.mp3 |}}
  
-We achieve this by first computing a //​self-similarity matrix// (SSM) of a feature representation of the song and identifying a segment in the recording that is frequently repeated. To account for the fact that the repetitions of the sample are most probably superimposed with other loops, we experimented with feature representations and distance measures ​which take this circumstance into account.+We achieve this by first computing a //​self-similarity matrix// (SSM) of a feature representation of the song and identifying a segment in the recording that is frequently repeated. To account for the fact that the repetitions of the sample are most probably superimposed with other loops, we experimented with different ​feature representations and distance measures.
  
  
 ===== Step 2: Find the Reoccurrences of the Identified Loop ===== ===== Step 2: Find the Reoccurrences of the Identified Loop =====
  
-Now, we need to identify the positions in the song where the identified loop is also present,+Now, we need to identify the positions in the song where the identified loop is also present.
  
 {{ :​step3.jpg?​nolink&​400 |}} {{ :​step3.jpg?​nolink&​400 |}}
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 ===== Step 3: Remove the Loop from the Song ===== ===== Step 3: Remove the Loop from the Song =====
  
-After knowing ​+Now, we remove the loop from the song at the identified time positions. This is done in the time-frequency domain, where we subtract the spectrogram of the loop point-wise from the spectrogram of the full song (we subtract the magnitudes, capping at 0, and use the phase information of the original song).
  
-{{ :step3.jpg?​nolink&​400 |}}+{{ :step4.jpg?​nolink&​400 |}}
  
-We do this by computing a //matching curve// and applying a //peak picking// scheme. Again, suitable feature representations and distance measures played an important role.+The //remainder// of the song — meaning the song without the loops — in our example sounds like this
  
-In our example, this is this loop+{{ :​Moby_Porcelain_Iteration1_Remainder.mp3 |}}
  
  
 +===== Step 4: Iterate =====
  
 +In the remainder of the song, we now hopefully have another loop that is occurring isolated. To remove this loop, we start from the beginning again.
  
 +{{ :​step5.jpg?​nolink&​400 |}}
  
 +In our example, the next loop to remove is
  
 +{{ :​Moby_Porcelain_Iteration2_Loop.mp3 |}}
  
-I.e. the task is: 
  
-  - Find a sample that's as //pure// as possible. 
-  - Removethe sample wherever it occurs in the song. 
-  - Repeat. 
  
-//Pure// in this context is shall mean //​standalone//,​ i.e. a sample that is not polluted by another sample yet. 
  
-===== Finding pure Samples ​=====+===== Results ​===== 
 +Here, you find the audio examples that we got from performing 3 Iterations of our procedure
  
-  - SSM (diagonal median filtered) +|Full song |{{:​Moby_Porcelain_FullSong.mp3|}}|
-  - Identify paths that have a certain length and length/​distance relationship +
-  - Pick a path according to the super-secret rules +
-  - Find similar locations in the song+
  
-To find similar locations in the song, we weren'​t able to use a regular cosine distance function, because we are not looking for absolute similarity, but rather a "​Sample A contains Sample B" relationship.+Iteration 1 : SynthPad 
 +|Loop|{{:​Moby_Porcelain_Iteration1_Loop.mp3|}}| 
 +|Remainder|{{:​Moby_Porcelain_Iteration1_Remainder.mp3|}}|
  
-===== Removing samples from the Song =====+Iteration 2 : Drums - soft 
 +|Loop|{{:​Moby_Porcelain_Iteration2_Loop.mp3|}}| 
 +|Remainder|{{:​Moby_Porcelain_Iteration2_Remainder.mp3|}}|
  
-In order to remove samples (loops) from the song, we simply subtract the magnitude spectrogram from the original spectrogram and re-synthesize both signal—the remains of the song and the sample we subtracted.+Iteration 2 : Drums strong 
 +|Loop|{{:​Moby_Porcelain_Iteration3_Loop.mp3|}}| 
 +|Remainder|{{:​Moby_Porcelain_Iteration3_Remainder.mp3|}}|
  
-===== Repeat ===== 
  
-We can continue this process for a number of iterations. Results get stranger and stranger... 
deconstructing_sample-based_electronic_dance_music.1445782790.txt.gz · Last modified: 2015/10/25 10:19 by jonathan