Improve dataset card: Add paper and code links, add 'benchmark' tag

This PR enhances the dataset card by adding direct links to the associated paper on Hugging Face Papers (`https://huggingface.co/papers/2409.08374`) and the GitHub repository (`https://github.com/JozefColdenhoff/OpenACE`) at the top of the README. This makes it easier for users to find the relevant research and code. It also adds the 'benchmark' tag to the metadata, aligning with the dataset's purpose as an open benchmark for evaluating audio coding performance.

README.md

@@ -1,10 +1,12 @@
 ---
+language:
+- en
 license: mit
+size_categories:
+- <1K
 task_categories:
 - audio-classification
 - audio-to-audio
-language:
-- en
 tags:
 - emotional-speech
 - audio-quality
@@ -13,12 +15,13 @@ tags:
 - mushra
 - visqol
 - polqa
-size_categories:
-- <1K
+- benchmark
 ---
 
 # EARS-EMO-OpenACE: A Full-band Coded Emotional Speech Quality Dataset
 
+[Paper](https://huggingface.co/papers/2409.08374) | [Code](https://github.com/JozefColdenhoff/OpenACE)
+
 ## Dataset Description
 
 This dataset contains full-band coded emotional speech samples at 16 kbps with human perceptual quality ratings and objective quality metrics. It is designed for research in audio quality assessment, emotion recognition, and codec evaluation.
@@ -167,4 +170,4 @@ If you use this dataset in your research, please cite the following [paper](http
 
 Milos Cernak, milos.cernak at ieee dot org
 
-August 1, 2025
+August 1, 2025