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Fix filter_cuts in compute_fbank_librispeech.py (#993)
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@ -121,10 +121,10 @@ def compute_fbank_librispeech(
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recordings=m["recordings"],
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supervisions=m["supervisions"],
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)
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if bpe_model:
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cut_set = filter_cuts(cut_set, sp)
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if "train" in partition:
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if bpe_model:
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cut_set = filter_cuts(cut_set, sp)
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cut_set = (
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cut_set + cut_set.perturb_speed(0.9) + cut_set.perturb_speed(1.1)
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)
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