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from speechbrain.pretrained import EncoderClassifier
class CustomEncoderWav2vec2Classifier(EncoderClassifier):
def compute_forward(self, batch, stage):
wavs, wav_lens = batch.sig
feats = self.mods.compute_features(wavs)
if self.mods.normalize:
feats = self.mods.normalize(feats, wav_lens)
x = self.mods.encoder(feats)
outputs = self.mods.classifier(x)
return outputs
def classify_file(self, path):
signal = self.load_audio(path)
batch = self.make_batch(signal)
probs = self.forward(batch)
score, index = probs.max(1)
label = self.hparams.label_encoder.decode(index)
return probs, score.item(), index.item(), label
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