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xlsr-wav2vec-speech-emotion-recognition
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Update README.md

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harshit katyal 2021-12-12 20:46:20 +00:00 committed by huggingface-web
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@ -65,4 +65,20 @@ outputs = predict(path, sampling_rate)
{'Emotion': 'fear', 'Score': '0.4%'}, {'Emotion': 'fear', 'Score': '0.4%'},
{'Emotion': 'happiness', 'Score': '0.7%'}, {'Emotion': 'happiness', 'Score': '0.7%'},
{'Emotion': 'sadness', 'Score': '0.5%'}] {'Emotion': 'sadness', 'Score': '0.5%'}]
~~~ ~~~
## Evaluation
The following tables summarize the scores obtained by model overall and per each class.
| Emotions | precision | recall | f1-score | accuracy |
|-----------|-----------|--------|----------|----------|
| anger | 0.82 | 1.00 | 0.81 | |
| disgust | 0.85 | 0.96 | 0.85 | |
| fear | 0.78 | 0.88 | 0.80 | |
| happiness | 0.84 | 0.71 | 0.78 | |
| sadness | 0.86 | 1.00 | 0.79 | |
| | | | Overall | 0.806 |
##