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asahi417
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seamless-align-enA-jaA.speaker-embedding.w2vbert-600m

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  1. README.md +32 -0
  2. subset_23/train-00000-of-00015.parquet +3 -0
  3. subset_23/train-00001-of-00015.parquet +3 -0
  4. subset_23/train-00002-of-00015.parquet +3 -0
  5. subset_23/train-00003-of-00015.parquet +3 -0
  6. subset_23/train-00004-of-00015.parquet +3 -0
  7. subset_23/train-00005-of-00015.parquet +3 -0
  8. subset_23/train-00006-of-00015.parquet +3 -0
  9. subset_23/train-00007-of-00015.parquet +3 -0
  10. subset_23/train-00008-of-00015.parquet +3 -0
  11. subset_23/train-00009-of-00015.parquet +3 -0
  12. subset_23/train-00010-of-00015.parquet +3 -0
  13. subset_23/train-00011-of-00015.parquet +3 -0
  14. subset_23/train-00012-of-00015.parquet +3 -0
  15. subset_23/train-00013-of-00015.parquet +3 -0
  16. subset_23/train-00014-of-00015.parquet +3 -0
README.md CHANGED
@@ -280,6 +280,34 @@ dataset_info:
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  num_examples: 1761
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  download_size: 7300894110
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  dataset_size: 7280210371
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - config_name: subset_3
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  features:
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  - name: line_no
@@ -489,6 +517,10 @@ configs:
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  data_files:
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  - split: train
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  path: subset_21/train-*
 
 
 
 
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  - config_name: subset_3
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  data_files:
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  - split: train
 
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  num_examples: 1761
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  download_size: 7300894110
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  dataset_size: 7280210371
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+ - config_name: subset_23
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+ features:
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+ - name: line_no
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+ dtype: int64
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+ - name: enA.id
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+ dtype: string
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+ - name: enA.laser_score
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+ dtype: float64
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+ - name: jaA.id
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+ dtype: string
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+ - name: jaA.laser_score
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+ dtype: float64
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+ - name: jaA.audio.speaker_embedding
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+ sequence: float32
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+ - name: jaA.audio.speaker_embedding.full
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+ sequence:
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+ sequence: float32
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+ - name: enA.audio.speaker_embedding
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+ sequence: float32
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+ - name: enA.audio.speaker_embedding.full
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+ sequence:
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+ sequence: float32
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+ splits:
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+ - name: train
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+ num_bytes: 7247343045
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+ num_examples: 1790
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+ download_size: 7268159959
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+ dataset_size: 7247343045
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  - config_name: subset_3
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  features:
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  - name: line_no
 
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  data_files:
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  - split: train
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  path: subset_21/train-*
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+ - split: train
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  data_files:
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