Answers.Body: <p>A first think what comes to mind is to train an autoencoder, then identify abnormal data by these heuristics:</p>
  <ul>
  <li>Is the reconstruction error large, for example remove the top 5% of the data?</li>
  <li>Are the codes (outputs of the encoder) within a densely populated region, or are they outliers? You could calculate the distance to Nth nearest neighbor.</li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-02-21T19:12:49.537Z
Answers.Text: Interesting idea, do you know any articles that has done that on audio or any kind of time series data?
Answers.UserDisplayName: Sepehr Golestanian
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-02-22T12:36:38.653Z
Answers.Text: I haven't read any of these papers, but I found plenty from Google Scolar by searching for "autoencoder outlier detection".
Answers.UserDisplayName: NikoNyrh
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-02-13T11:53:08.353Z
Answers.LastActivityDate: 2022-02-13T11:53:08.353Z
Answers.UserDisplayName: NikoNyrh
Body: <p>I'm currently working on an audio classification project using CNNs. The problem is I'm having trouble training my CNN. I doubt if there are outliers in my dataset but I don't know how to detect outliers in an <strong>audio dataset</strong>. I've searched google and found nothing helpful.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-02-13T11:12:17.547Z
Comments.Text: Tell us what you have found so far and why it's not helpful. Explain also exactly what you're looking for.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-02-21T19:11:09.967Z
Comments.Text: @nbro almost everything I found on google was about finding outliers in tabular data, therefore, they're not applicable to audio or any kind of time series data.
Comments.UserDisplayName: Sepehr Golestanian
Tags: <data-preprocessing>
Title: how to detect ouliers in audio dataset?
UserDisplayName: Sepehr Golestanian
ThreadText: # how to detect ouliers in audio dataset?
  
  (Asked by: username_0 on 2022-02-13)
  
  I'm currently working on an audio classification project using CNNs. The problem is I'm having trouble training my CNN. I doubt if there are outliers in my dataset but I don't know how to detect outliers in an **audio dataset**. I've searched google and found nothing helpful.
  
  **Tags:** data-preprocessing
  
  > **Comments:**
  > **username_1**: Tell us what you have found so far and why it's not helpful. Explain also exactly what you're looking for.  
  > **username_0**: @username_1 almost everything I found on google was about finding outliers in tabular data, therefore, they're not applicable to audio or any kind of time series data.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2022-02-13. Score: 1
  
  A first think what comes to mind is to train an autoencoder, then identify abnormal data by these heuristics:
  
  * Is the reconstruction error large, for example remove the top 5% of the data?
  * Are the codes (outputs of the encoder) within a densely populated region, or are they outliers? You could calculate the distance to Nth nearest neighbor.
  
  > **Comments:**
  > **username_0**: Interesting idea, do you know any articles that has done that on audio or any kind of time series data?  
  > **username_2**: I haven't read any of these papers, but I found plenty from Google Scolar by searching for "autoencoder outlier detection".  
  
  ---
  
  