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@@ -8,6 +8,7 @@ datasets:
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  - openslr/librispeech_asr
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  metrics:
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  - wer
 
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  model-index:
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  - name: SpeechLLM
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  results:
@@ -23,7 +24,7 @@ model-index:
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  language: en
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  metrics:
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  - type: wer
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- value: 12.3
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  name: Test WER
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  - task:
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  type: automatic-speech-recognition
@@ -37,7 +38,7 @@ model-index:
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  language: en
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  metrics:
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  - type: wer
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- value: 18.9
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  name: Test WER
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  - task:
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  type: automatic-speech-recognition
@@ -50,8 +51,34 @@ model-index:
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  language: en
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  metrics:
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  - type: wer
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- value: 25.01
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  name: Test WER
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # SpeechLLM
 
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  - openslr/librispeech_asr
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  metrics:
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  - wer
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+ - accuracy
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  model-index:
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  - name: SpeechLLM
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  results:
 
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  language: en
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  metrics:
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  - type: wer
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+ value: 7.3
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  name: Test WER
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  - task:
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  type: automatic-speech-recognition
 
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  language: en
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  metrics:
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  - type: wer
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+ value: 10.47
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  name: Test WER
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  - task:
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  type: automatic-speech-recognition
 
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  language: en
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  metrics:
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  - type: wer
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+ value: 24.47
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  name: Test WER
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+ - task:
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+ type: audio-classification
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+ name: Audio Classification
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+ dataset:
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+ name: Common Voice 16.1
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+ type: common_voice_16_1
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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: accuracy
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+ value: 60.61
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+ name: Test Age Accuracy
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+ - task:
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+ type: audio-classification
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+ name: Audio Classification
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+ dataset:
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+ name: Common Voice 16.1
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+ type: common_voice_16_1
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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: accuracy
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+ value: 61.56
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+ name: Test Accent Accuracy
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  ---
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  # SpeechLLM