Update README

README.md

@@ -9,7 +9,6 @@ pretty_name: GTZAN
   - [Table of Contents](#table-of-contents)
   - [Dataset Description](#dataset-description)
     - [Dataset Summary](#dataset-summary)
-    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
     - [Languages](#languages)
   - [Dataset Structure](#dataset-structure)
     - [Data Instances](#data-instances)
@@ -36,31 +35,56 @@ pretty_name: GTZAN
 
 ## Dataset Description
 
-- **Homepage:** http://marsyas.info/downloads/datasets.html
-- **Paper:** http://ismir2001.ismir.net/pdf/tzanetakis.pdf
+- **Homepage:** [http://marsyas.info/downloads/datasets.html](http://marsyas.info/downloads/datasets.html)
+- **Paper:** [http://ismir2001.ismir.net/pdf/tzanetakis.pdf](http://ismir2001.ismir.net/pdf/tzanetakis.pdf)
 - **Point of Contact:** 
 
 ### Dataset Summary
 
-[More Information Needed]
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed]
+GTZAN is a dataset for musical genre classification of audio signals. The dataset consists of 1,000 audio tracks, each of 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22,050Hz Mono 16-bit audio files in WAV format. The genres are: blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, and rock.
 
 ### Languages
 
-[More Information Needed]
+English
 
 ## Dataset Structure
 
+GTZAN is distributed as a single dataset without a predefined training and test split. The information below refers to the single `train` split that is assigned by default.
+
 ### Data Instances
 
-[More Information Needed]
+An example of GTZAN looks as follows:
+
+```python
+{
+    "file": "/path/to/cache/genres/blues/blues.00000.wav",
+    "audio": {
+        "path": "/path/to/cache/genres/blues/blues.00000.wav",
+        "array": array(
+            [
+                0.00732422,
+                0.01660156,
+                0.00762939,
+                ...,
+                -0.05560303,
+                -0.06106567,
+                -0.06417847,
+            ],
+            dtype=float32,
+        ),
+        "sampling_rate": 22050,
+    },
+    "genre": 0,
+}
+```
 
 ### Data Fields
 
-[More Information Needed]
+The types associated with each of the data fields is as follows:
+
+* `file`: a `string` feature.
+* `audio`: an `Audio` feature containing the `path` of the sound file, the decoded waveform in the `array` field, and the `sampling_rate`.
+* `genre`: a `ClassLabel` feature.
 
 ### Data Splits
 
@@ -122,7 +146,15 @@ pretty_name: GTZAN
 
 ### Citation Information
 
-[More Information Needed]
+```
+@misc{tzanetakis_essl_cook_2001,
+author    = "Tzanetakis, George and Essl, Georg and Cook, Perry",
+title     = "Automatic Musical Genre Classification Of Audio Signals",
+url       = "http://ismir2001.ismir.net/pdf/tzanetakis.pdf",
+publisher = "The International Society for Music Information Retrieval",
+year      = "2001"
+}
+```
 
 ### Contributions
 

gtzan.py

@@ -11,13 +11,9 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-# TODO: Address all TODOs and remove all explanatory comments
-"""TODO: Add a description here."""
+"""The GTZAN dataset."""
 
 
-import csv
-import json
-import os
 from pathlib import Path
 
 import datasets
@@ -35,7 +31,7 @@ year      = "2001"
 
 
 _DESCRIPTION = """\
-GTZAN is a dataset for musical genre classification of audio signals. The dataset consists of 1,000 audio tracks, each of 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22,050Hz Mono 16-bit audio files in .wav format. The genres are: blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, and rock.
+GTZAN is a dataset for musical genre classification of audio signals. The dataset consists of 1,000 audio tracks, each of 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22,050Hz Mono 16-bit audio files in WAV format. The genres are: blues, classical, country, disco, hiphop, jazz, metal, pop, reggae, and rock.
 """
 
 _HOMEPAGE = "http://marsyas.info/downloads/datasets.html"
@@ -50,7 +46,7 @@ CORRUPTED_FILES = ["jazz.00054.wav"]
 
 
 class Gtzan(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
+    """The GTZAn dataset"""
 
     def _info(self):
         return datasets.DatasetInfo(