Update README.md

README.md

@@ -16,18 +16,18 @@ tags:
 We present the BirdSet benchmark that covers a comprehensive range of 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.
 
-|                                     | train (#recordings)   |    test    | test_5s |  size (GB) |   #classes   |
-|-------------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
-| [PER][1] (Amazon Basin)             |  16,802 |     14,798 |  15,120 |   10.5     |     132      |
-| [NES][2] (Colombia Costa Rica)      |  16,117 |      6,952 |  24,480 |   14.2     |      89      |
-| [UHH][3] (Hawaiian Islands)         |  3,626  |     59,583 |  36,637 |   4.92     | 25 tr, 27 te |
-| [HSN][4] (high_sierras)             |  5,460  |     10,296 |  12,000 |   5.92     |      21      |
-| [NBP][5] (NIPS4BPlus)               |  24,327 |      5,493 |     563 |   29.9     |      51      |
-| [POW][6] (Powdermill Nature)        |  14,911 |     16,052 |   4,560 |   15.7     |      48      |
-| [SSW][7] (Sapsucker Woods)          |  28,403 |     50,760 |  205,200|   35.2     |      81      |
-| [SNE][8] (Sierra Nevada)            |  19,390 |     20,147 |  23,756 |   20.8     |      56      |
-| [XCM][9] (Xenocanto Subset M)       |  89,798 |       x    |     x   |   89.3     |    409       |
-| [XCL][10](Xenocanto Subset Complete)|  528,434|       x    |     x   |   484      |   9,734      |
+|                                | train   |    test    | test_5s |  size (GB) |   #classes   |
+|--------------------------------|--------:|-----------:|--------:|-----------:|-------------:|
+| [PER][1] (Amazon Basin)        |  16,802 |     14,798 |  15,120 |   10.5     |     132      |
+| [NES][2] (Colombia Costa Rica) |  16,117 |      6,952 |  24,480 |   14.2     |      89      |
+| [UHH][3] (Hawaiian Islands)    |  3,626  |     59,583 |  36,637 |   4.92     | 25 tr, 27 te |
+| [HSN][4] (high_sierras)        |  5,460  |     10,296 |  12,000 |   5.92     |      21      |
+| [NBP][5] (NIPS4BPlus)          |  24,327 |      5,493 |     563 |   29.9     |      51      |
+| [POW][6] (Powdermill Nature)   |  14,911 |     16,052 |   4,560 |   15.7     |      48      |
+| [SSW][7] (Sapsucker Woods)     |  28,403 |     50,760 |  205,200|   35.2     |      81      |
+| [SNE][8] (Sierra Nevada)       |  19,390 |     20,147 |  23,756 |   20.8     |      56      |
+| [XCM][9] (Xenocanto Subset M)  |  89,798 |       x    |     x   |   89.3     |      409     |
+| [XCL][10](Xenocanto Complete)  |  528,434|       x    |     x   |   484      |      9,734   |
 
 [1]:  https://zenodo.org/records/7079124
 [2]:  https://zenodo.org/records/7525349
@@ -40,6 +40,11 @@ We offer a static set of evaluation datasets and a varied collection of training
 [9]:  https://xeno-canto.org/
 [10]: https://xeno-canto.org
 
+- We assemble a training dataset for each test dataset that is a subset of a complete XC snapshot. We extract all recordings that have vocalizations of the bird species appearing in the test dataset.
+- Each sample in the training dataset is a recording may have more than one vocalization of the corresponding bird species.
+- We omit all recordings from XC that are CC-ND.
+- Snapshot date of XC: 03/10/2024
+- 
 ##### Train
 - Exclusively using focal audio data from Xeno-Canto (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 soundscape files.