Answers.Body: <p>It is possible to use spectrograms for genres classification. See relevant articles <a href="https://ieeexplore.ieee.org/document/5977391/" rel="nofollow noreferrer">Music genre recognition using spectrograms</a> or blog post <a href="http://deepsound.io/music_genre_recognition.html" rel="nofollow noreferrer">here</a>. The later link did use CNN for this task. </p>
  
  <p>If you need training data, <a href="http://marsyasweb.appspot.com/download/data_sets/" rel="nofollow noreferrer">GTZAN</a> or <a href="https://github.com/mdeff/fma" rel="nofollow noreferrer">FMA</a> could be your starting point.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-05-07T19:12:39.283Z
Answers.LastActivityDate: 2018-05-07T19:12:39.283Z
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Body: <p>Is it possible to categories songs based on their spectrograms using image recognition or would there need to  more features? I was thinking that the spectrograms might also run into problems with EDM songs. Such as House music being closely related to their sounds. Would there have to be immense amount of data? I was thinking of using a CNN.</p>
  
Tags: <neural-networks><machine-learning><classification>
Title: Is it possible to classify songs by genres based on spectrograms?
UserDisplayName: Slightly Higher Average User
ThreadText: # Is it possible to classify songs by genres based on spectrograms?
  
  (Asked by: username_0 on 2018-05-07)
  
  Is it possible to categories songs based on their spectrograms using image recognition or would there need to more features? I was thinking that the spectrograms might also run into problems with EDM songs. Such as House music being closely related to their sounds. Would there have to be immense amount of data? I was thinking of using a CNN.
  
  **Tags:** neural-networks, machine-learning, classification
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2018-05-07. Score: 3 | Accepted answer
  
  It is possible to use spectrograms for genres classification. See relevant articles [Music genre recognition using spectrograms](https://ieeexplore.ieee.org/document/5977391/) or blog post [here](http://deepsound.io/music_genre_recognition.html). The later link did use CNN for this task.
  
  If you need training data, [GTZAN](http://marsyasweb.appspot.com/download/data_sets/) or [FMA](https://github.com/mdeff/fma) could be your starting point.
  
  
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