Update README.md

README.md

@@ -17,13 +17,40 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 24342896.0
+    num_bytes: 24342896
     num_examples: 887
   download_size: 22503144
-  dataset_size: 24342896.0
+  dataset_size: 24342896
 configs:
 - config_name: default
   data_files:
   - split: train
     path: data/train-*
+license: cc
+tags:
+- avian-perceptual-judgment
+- audio-perceptual-judgment
+size_categories:
+- n<1K
 ---
+# Dataset Card for VocSim - Avian Perception Alignment
+
+## Dataset Description
+
+This dataset is a used in the **VocSim** paper, specifically designed to evaluate how well neural audio embeddings align with biological perceptual judgments of similarity. It utilizes data from Zandberg et al. (2024)~\cite{zandberg2024bird}, which includes recordings of zebra finch (*Taeniopygia guttata*) song syllables and results from behavioral experiments (probe and triplet tasks) measuring the birds' perception of syllable similarity.
+
+## Dataset Structure
+
+### Data Instances
+
+A typical example in the dataset looks like this:
+
+```python
+{
+  'audio': {'path': '/path/to/datasets/avian_perception/wavs/ZF_M_123_syllable_A.wav', 'array': array([-0.00024414, -0.00048828, ...,  0.00024414], dtype=float32), 'sampling_rate': 16000},
+  'subset': 'avian_perception',
+  'index': 42,
+  'speaker': 'ZF_M_123',
+  'label': 'ZF_M_123', # Label is set to speaker ID for this dataset
+  'original_name': 'ZF_M_123_syllable_A.wav' # Identifier as used in CSVs
+}