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README.md

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 pretty_name: B(asic) E(motion) R(andom phrase) S(hou)t(s)
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 - 1K<n<10K
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+---
+
+
+# BERSt Dataset
+
+We release the BERSt Dataset for various speech recognition tasks including Automatic Speech Recognition (ASR) and Speech Emotion Recogniton (SER)
+
+## Overview
+
+* 9207 single phrase recordings (~12h)
+* 96 professional actors
+* 19 phone positions
+* 7 emotion classes
+* 3 vocal intensity levels
+* varied regional and non-native English accents
+* nonsense phrases covering all English Phonemes
+
+## Data collection
+
+The BERSt dataset represents data collected in home envrionments using various smartphone microphones (phone model available as metadata)
+Participants were 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
+
+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