Update README.md

README.md

@@ -14,7 +14,7 @@ datasets:
 - voxceleb
 metrics:
 - EER
-- min_dct
+
 ---
 
 # Speaker Verification with ECAPA-TDNN embeddings on Voxceleb
@@ -61,10 +61,8 @@ embeddings = verification.encode_batch(signal)
 ```python
 import torchaudio
 from speechbrain.pretrained import SpeakerRecognition
-verification = SpeakerRecognition.from_hparams(source="speechbrain/spkrec-ecapa-voxceleb", savedir="pretrained_models/spkrec-ecapa-voxceleb)
-signal, fs =torchaudio.load('samples/audio_samples/example1.wav')
-signal2, fs = torchaudio.load('samples/audio_samples/example2.flac')
-score, prediction = verification.verify_batch(signal, signal2)
+verification = SpeakerRecognition.from_hparams(source="speechbrain/spkrec-ecapa-voxceleb", savedir="pretrained_models/spkrec-ecapa-voxceleb")
+score, prediction = verification.verify_files("speechbrain/spkrec-ecapa-voxceleb/example1.wav", "speechbrain/spkrec-ecapa-voxceleb/example2.flac")
 ```
  The prediction is 1 if the two signals in input are from the same speaker and 0 otherwise.