Update README.md

README.md

@@ -37,15 +37,15 @@ We release the BERSt Dataset for various speech recognition tasks including Auto
 
 ## Data collection
 
-The BERSt dataset represents data collected in home envrionments using various smartphone microphones (phone model available as metadata)
+The BERSt dataset represents data collected in home environments using various smartphone microphones (phone model available as metadata)
 The recordings come from professional actors around the globe and represent varying regional accents in English: UK, Canada, USA (multi-state), Australia, including a subset of the data that is non-native English speakers including: French, Russian, Hindi etc.
-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
+The data includes 13 non-sense phrases for use cases robust to linguistic context and high surprisal.
+Participants 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 conditions 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.
+Affect annotations are those provided to the actors; they have not been validated through perception.
+The speech annotations, however, have been checked and adjusted for mistakes in the speech.
 
 ## Data splits and organisation