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From GitBox <...@apache.org>
Subject [GitHub] NRauschmayr commented on a change in pull request #14179: Fix READMEs for examples
Date Sat, 16 Feb 2019 00:29:55 GMT
NRauschmayr commented on a change in pull request #14179: Fix READMEs for examples
URL: https://github.com/apache/incubator-mxnet/pull/14179#discussion_r257432986
 
 

 ##########
 File path: example/gluon/audio/README.md
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 @@ -0,0 +1,100 @@
+# Urban Sounds Classification in MXNet Gluon
+
+This example provides an end-to-end pipeline for a common datahack competition - Urban Sounds
Classification Example.
+Below is the link to the competition:
+https://datahack.analyticsvidhya.com/contest/practice-problem-urban-sound-classification/
+
+After logging in, the data set can be downloaded.
+The details of the dataset and the link to download it are given below:
+
+
+## Urban Sounds Dataset:
+### Description
+  The dataset contains 8732 wav files which are audio samples(<= 4s)) of street sounds
like engine_idling, car_horn, children_playing, dog_barking and so on.
+  The task is to classify these audio samples into one of the following 10 labels:
+  ```
+  siren,
+  street_music,
+  drilling,
+  dog_bark,
+  children_playing,
+  gun_shot,
+  engine_idling,
+  air_conditioner,
+  jackhammer,
+  car_horn
+  ```
+
+To be able to run this example:
+
+1. `pip install -r requirements.txt`
+
+    If you are in the directory where the requirements.txt file lies,
+    this step installs the required libraries to run the example.
+    The main dependency that is required is: Librosa. 
+    The version used to test the example is: `0.6.2`
+    For more details, refer here:
+https://librosa.github.io/librosa/install.html
+
+2. Download the dataset(train.zip, test.zip) required for this example from the location:
+https://drive.google.com/drive/folders/0By0bAi7hOBAFUHVXd1JCN3MwTEU
+
 
 Review comment:
   I agree with you. We need to figure out what the license of the dataset is. I assume the
original files are from here https://datahack.analyticsvidhya.com/contest/practice-problem-urban-sound-classification/#data_dictionary
   And the Google drive link belongs to someone from analyticsvidhya, so maybe this link is
the official source?
    

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