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README.md
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language: en
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metrics:
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- type: wer
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value:
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name: Test WER
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: ML Spoken Words
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type: MLCommons/ml_spoken_words
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split: test
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args:
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language: en
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metrics:
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- type: wer
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value: 36.12
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name: Test WER
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: IEMOCAP
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type: Ar4ikov/iemocap_audio_text_splitted
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split: test
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args:
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language: en
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metrics:
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- type: wer
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value: 44.15
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name: Test WER
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type: audio-classification
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language: en
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metrics:
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- type: accuracy
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value:
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name: Test Age Accuracy
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- type: accuracy
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value:
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name: Test Accent Accuracy
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---
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@@ -160,8 +134,6 @@ Try the model in [Google Colab Notebook](https://colab.research.google.com/drive
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| **Dataset** | **Type** | **Word Error Rate** | **Gender Acc** | **Age Acc** | **Accent Acc** |
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|:--------------------------:|:-------------------:|:-------------------:|:--------------:|:-----------:|:--------------:|
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| **librispeech-test-clean** | Read Speech | 6.73 | 0.
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| **librispeech-test-other** | Read Speech | 9.13 | 0.
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| **CommonVoice test** | Diverse Accent, Age |
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| **ML Spoken Words test** | Short Utterance | 36.12 | 0.6587 | | |
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| **IEMOCAP test** | Emotional Speech | 44.15 | 0.7557 | | |
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language: en
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metrics:
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- type: wer
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value: 26.02
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name: Test WER
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- task:
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type: audio-classification
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language: en
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metrics:
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- type: accuracy
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value: 60.41
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name: Test Age Accuracy
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- type: accuracy
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value: 69.59
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name: Test Accent Accuracy
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---
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| **Dataset** | **Type** | **Word Error Rate** | **Gender Acc** | **Age Acc** | **Accent Acc** |
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|:--------------------------:|:-------------------:|:-------------------:|:--------------:|:-----------:|:--------------:|
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| **librispeech-test-clean** | Read Speech | 6.73 | 0.9496 | | |
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| **librispeech-test-other** | Read Speech | 9.13 | 0.9217 | | |
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| **CommonVoice test** | Diverse Accent, Age | 26.02 | 0.8680 | 0.6041 | 0.6959 |
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