Add metadata and split information

README.md

@@ -25,8 +25,8 @@ We release the BERSt Dataset for various speech recognition tasks including Auto
 
 ## Overview
 
-* 9207 single phrase recordings (~12h)
-* 96 professional actors
+* 4526 single phrase recordings (~12h)
+* 98 professional actors
 * 19 phone positions
 * 7 emotion classes
 * 3 vocal intensity levels
@@ -40,4 +40,65 @@ Participants were around the globe and represent varying regional accents in Eng
 The data includes 13 non-sense phrases for use cases robust to lingustic context and high surprisal.
 Partipants were prompted to speak, raise their voice and shout each phrase while moving their phone to various distances and locations in their home, as well as with various obstructions to the microphone, e.g. in a backpack
 
-Baseline results of various state-of-the-art methods for ASR and SER show that this dataset remains a challenging task, and we encourage researchers to use this data to fine-tune and benchmark their models in these difficult condition representing possible real world situations
+Baseline results of various state-of-the-art methods for ASR and SER show that this dataset remains a challenging task, and we encourage researchers to use this data to fine-tune and benchmark their models in these difficult condition representing possible real world situations
+
+Affect annotations are those provided to the actors, they have not been validated through perception
+The speech annotations, however, has been checked and adjusted to mistakes in the speech.
+
+## Data splits and organisation
+
+For each phone position and phrase, the actors provided a single recording for the three vocal intensity levels, these raw audio files are available
+
+Meta-data in csv format corresponds to the files split per utterance, found inside `clean_clips` for each data splits
+
+We provide a test, train and validation split
+
+There is no speaker cross-over between splits, the train and validation sets each contain 10 speakers not seen in the training set
+
+## Baseline Results
+TBD
+
+## Metadata Details
+
+* actor count
+  * 98
+* Gender counts
+  * Woman: 61
+  * Man: 34
+  * Non-Binary: 1
+  * Prefer not to disclose 2
+* Current daily language counts
+  * English: 95
+  * Norwegian: 1
+  * Russian: 1
+  * French: 1
+* First language counts
+  * English: 75
+  * Non English: 23
+    * Spanish: 6
+    * French: 3
+    * Portuguese: 3
+    * Chinese: 2
+    * Norwegian: 1
+    * Mandarin: 1
+    * Tagalog: 1
+    * Italian: 1
+    * Hungarian: 1
+    * Russian: 1
+    * Hindi: 1
+    * Swahili: 1
+    * Croatian: 1
+Pre-split Data counts
+* Emotion counts
+  * fear: 236
+  * neutral: 234
+  * disgust: 232
+  * joy: 224
+  * anger: 223
+  * surprise: 210
+  * sadness: 201
+* Distance counts:
+  * Near body: 627
+  * 1-2m away: 324
+  * Other side of room: 316
+  * Outside of room: 293