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@@ -168,7 +168,7 @@ print(prediction[3])
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  ['th']
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  # Alternatively, use the utterance embedding extractor:
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- emb = language_id.encode_batch(signal_resampled)
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  print(emb.shape)
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  torch.Size([1, 1, 256])
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  ```
@@ -208,7 +208,7 @@ Error rate: 7% on the development dataset
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  ```bibtex
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  @inproceedings{valk2021slt,
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  title={{VoxLingua107}: a Dataset for Spoken Language Recognition},
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- author={J{\\"o}rgen Valk and Tanel Alum{\\"a}e},
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  booktitle={Proc. IEEE SLT Workshop},
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  year={2021},
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  }
 
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  ['th']
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  # Alternatively, use the utterance embedding extractor:
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+ emb = language_id.encode_batch(signal)
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  print(emb.shape)
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  torch.Size([1, 1, 256])
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  ```
 
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  ```bibtex
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  @inproceedings{valk2021slt,
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  title={{VoxLingua107}: a Dataset for Spoken Language Recognition},
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+ author={J{\"o}rgen Valk and Tanel Alum{\"a}e},
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  booktitle={Proc. IEEE SLT Workshop},
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  year={2021},
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  }