Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


  • Description:

The dataset consists of 1000 audio tracks each 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22050Hz Mono 16-bit audio files in .wav format.

The genres are:

Split Examples
'train' 1,000
  • Features:
    'audio': Audio(shape=(None,), dtype=tf.int64),
    'audio/filename': Text(shape=(), dtype=tf.string),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=10),
  • Citation:
author    = "Tzanetakis, George and Essl, Georg and Cook, Perry",
title     = "Automatic Musical Genre Classification Of Audio Signals",
url       = "",
publisher = "The International Society for Music Information Retrieval",
year      = "2001"