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Update README.md

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@@ -63,6 +63,8 @@ classifier = EncoderClassifier.from_hparams(source="speechbrain/spkrec-ecapa-vox
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  signal, fs =torchaudio.load('samples/audio_samples/example1.wav')
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  embeddings = classifier.encode_batch(signal)
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  ```
 
 
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  ### Perform Speaker Verification
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  signal, fs =torchaudio.load('samples/audio_samples/example1.wav')
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  embeddings = classifier.encode_batch(signal)
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  ```
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+ The system is trained with recordings sampled at 16kHz (single channel).
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+ The code will automatically normalize your audio (i.e., resampling + mono channel selection) when calling *classify_file* if needed. Make sure your input tensor is compliant with the expected sampling rate if you use *encode_batch* and *classify_batch*.
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  ### Perform Speaker Verification
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