Improve dataset card: Add task category, abstract summary, links, and sample usage

This PR significantly enhances the dataset card for the Differentiable Vocal Effects Presets Dataset by:
- Adding `audio-to-audio` to the `task_categories` and `vocal-effects` to the `tags` metadata for improved discoverability.
- Incorporating a summary of the paper's abstract to provide better context for the dataset.
- Consolidating relevant links (Paper, Code, Demo) into a dedicated "Links" section for easier navigation.
- Including a "Sample Usage" section with a quick start guide extracted from the GitHub repository, enabling users to more easily get started with the dataset.

README.md

@@ -1,17 +1,45 @@
 ---
 license: mit
-tags:
-- music
 size_categories:
 - n<1K
+tags:
+- music
+- vocal-effects
+task_categories:
+- audio-to-audio
 viewer: false
 ---
 
 # Differentiable Vocal Effects Presets Dataset
 
-This dataset is a clone of a subset of the [diffvox](https://github.com/SonyResearch/diffvox/) repository, containing a collection of vocal effect presets derived from a proprietary multitrack dataset, as described in the paper [DiffVox: A Differentiable Model for Capturing and Analysing Professional Effects Distributions](https://arxiv.org/abs/2504.14735). 
+This dataset is associated with DiffVox, a novel and interpretable model designed for matching vocal effects in music production. DiffVox integrates parametric equalisation, dynamic range control, delay, and reverb using efficient differentiable implementations, enabling gradient-based optimisation for parameter estimation. The vocal presets contained within this dataset were retrieved from two collections: 70 tracks from MedleyDB and 365 tracks from a private collection. This work lays the foundation for future research in vocal effects modelling and automatic mixing.
+
+This dataset is a clone of a subset of the [diffvox](https://github.com/SonyResearch/diffvox/) repository, containing a collection of vocal effect presets derived from a proprietary multitrack dataset.
+
+## Links
+- Paper: [DiffVox: A Differentiable Model for Capturing and Analysing Vocal Effects Distributions](https://arxiv.org/abs/2504.14735)
+- Code: [https://github.com/SonyResearch/diffvox](https://github.com/SonyResearch/diffvox)
+- Demo Space: [https://huggingface.co/spaces/yoyolicoris/diffvox](https://huggingface.co/spaces/yoyolicoris/diffvox)
+
+## Dataset Structure
 
 The preset datasets, **Internal** and **MedleyDB**, are stored in the folder [`presets`](presets/).
 Please check the original repository for more details on the individual files.
 The [modules/](modules/) contains differentiable effects implemented in PyTorch for loading the presets and applying them to audio data.
-For concrete examples of how to use the dataset, please refer to our [demo](https://huggingface.co/spaces/yoyolicoris/diffvox).
+
+## Sample Usage
+
+For concrete examples of how to use the dataset and its associated code, please refer to the original GitHub repository. Below is a quick start example demonstrating how to set up the environment and run the retrieval process on a single track:
+
+First, install the required Python packages by cloning the original repository and installing its requirements:
+```bash
+git clone https://github.com/SonyResearch/diffvox.git
+cd diffvox
+pip install -r requirements.txt
+```
+
+Then, you can run the vocal effects retrieval process on a specific track. For example, to process a track from MedleyDB:
+```bash
+python main.py data_dir=/data/medley1/v1/Audio/AimeeNorwich_Child --dataset=medley_vocal --log_dir=~/medley_vocal_log
+```
+This command will run the retrieval process on valid vocal tracks within the specified directory and save the training logs and best checkpoints to `~/medley_vocal_log`. Refer to the original repository's `main.py` and `cfg/config.yaml` for configuration details.