Update README.md

README.md

@@ -26,18 +26,41 @@ configs:
   data_files:
   - split: train
     path: data/train-*
-license: cc
+license: cc-by-4.0 # Explicitly CC-BY 4.0 based on PLoS Comp Bio policy
 tags:
+- audio
+- animal-vocalization
+- birdsong
+- zebra-finch
+- perceptual-similarity
+- benchmark
+- zero-shot
+- vocsim
 - avian-perceptual-judgment
 - audio-perceptual-judgment
 size_categories:
 - n<1K
+pretty_name: "VocSim - Avian Perception Alignment"
 ---
+
 # 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.
+This dataset is used in the **VocSim benchmark** 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)**, 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.
+
+The dataset allows researchers to:
+1.  Extract features/embeddings from the song syllables using various computational models.
+2.  Compute pairwise distances between these embeddings.
+3.  Compare the resulting computational similarity matrices against the avian perceptual judgments recorded in the accompanying `probes.csv` and `triplets.csv` files.
+
+This facilitates the development and benchmarking of audio representations that better capture biologically relevant acoustic features.
+
+**Included Files:**
+*   Hugging Face `Dataset` object containing audio file paths and metadata.
+*   `probes.csv`: Contains results from perceptual probe trials (sound_id, left, right, decision, etc.). Filtered to include only rows where all mentioned audio files exist.
+*   `triplets.csv`: Contains results from perceptual triplet trials (Anchor, Positive, Negative, diff, etc.). Filtered to include only rows where all mentioned audio files exist.
+*   `missing_audio_files.txt` (optional): Lists identifiers from the original CSVs for which no corresponding audio file was found.
 
 ## Dataset Structure
 
@@ -54,3 +77,29 @@ A typical example in the dataset looks like this:
   '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
 }
+```
+## Citation Information
+
+If you use this dataset in your work, please cite both the VocSim benchmark paper and the original source data paper:
+
+```bib
+@unpublished{vocsim2025,
+  title={VocSim: Zero-Shot Audio Similarity Benchmark for Neural Embeddings},
+  author={Anonymous},
+  year={2025},
+  note={Submitted manuscript}
+}
+
+@article{zandberg2024bird,
+  author = {Zandberg, Lies and Morfi, Veronica and George, Julia M. and Clayton, David F. and Stowell, Dan and Lachlan, Robert F.},
+  title = {Bird song comparison using deep learning trained from avian perceptual judgments},
+  journal = {PLoS Computational Biology},
+  volume = {20},
+  number = {8},
+  year = {2024},
+  month = {aug},
+  pages = {e1012329},
+  doi = {10.1371/journal.pcbi.1012329},
+  publisher = {Public Library of Science}
+}
+```