Update README.md

README.md

@@ -12,14 +12,16 @@ tags:
 - **Paper:** [BirdSet](https://arxiv.org/abs/2403.10380)
 - **Point of Contact:** [Lukas Rauch](mailto:lukas.rauch@uni-kassel.de)
 
-
-## Datasets
-We present the BirdSet benchmark that covers a comprehensive range of (multi-label and multi-class) classification datasets in avian bioacoustics. 
-We offer a static set of evaluation datasets and a varied collection of training datasets, enabling the application of diverse methodologies.
+## BirdSet
+Deep learning models have emerged as a powerful tool in avian bioacoustics to assess environmental health. To maximize the potential of cost-effective and minimal-invasive 
+passive acoustic monitoring (PAM), models must analyze bird vocalizations across a wide range of species and environmental conditions. However, data fragmentation 
+challenges a evaluation of generalization performance. Therefore, we introduce the BirdSet dataset, comprising approximately 520,000 global bird recordings 
+for training and over 400 hours PAM recordings for testing.
 - **Complementary Code**:[https://github.com/DBD-research-group/GADME](https://github.com/DBD-research-group/BirdSet)
 - **Complementary Paper**: [https://arxiv.org/abs/2403.10380](https://arxiv.org/abs/2403.10380)
 
 
+## Datasets
 |                                | train   |    test    | test_5s |  size (GB) |   #classes   |    license    |
 |--------------------------------|--------:|-----------:|--------:|-----------:|-------------:|--------------:|
 | [PER][1] (Amazon Basin)        |  16,802 |     14,798 |  15,120 |   10.5     |     132      |   CC-BY-4.0   |  
@@ -52,6 +54,8 @@ We offer a static set of evaluation datasets and a varied collection of training
 - The bird species are translated to ebird_codes
 - Snapshot date of XC: 03/10/2024
 
+Each dataset (except for XCM and XCL that only feature Train) comes with a dataset dictionary that features **Train**, **Test_5s**, and **Test**: 
+
 **Train**
 - Exclusively using focal audio data from XC with quality ratings A, B, C and excluding all recordings that are CC-ND.
 - Each dataset is tailored for specific target species identified in the corresponding test soundscape files.
@@ -72,7 +76,7 @@ We offer a static set of evaluation datasets and a varied collection of training
 - This dataset excludes recordings that do not contain bird calls ("no_call").
 
 # How to
-- We recommend to use our [intro notebook](https://github.com/DBD-research-group/BirdSet/blob/main/notebooks/tutorials/birdset-pipeline_tutorial.ipynb) in our code repository
+- We recommend to use our [intro notebook](https://github.com/DBD-research-group/BirdSet/blob/main/notebooks/tutorials/birdset-pipeline_tutorial.ipynb) in our code repository.
 - The BirdSet Code package simplfies the data processing steps 
 - For multi-label evaluation with a segment-based evaluation use the test_5s column for testing.