import torch
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from torch.nn.utils.rnn import pad_sequence
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def slice_padding_fbank(speech, speech_lengths, vad_segments):
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speech_list = []
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speech_lengths_list = []
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for i, segment in enumerate(vad_segments):
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bed_idx = int(segment[0][0]*16)
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end_idx = min(int(segment[0][1]*16), speech_lengths[0])
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speech_i = speech[0, bed_idx: end_idx]
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speech_lengths_i = end_idx-bed_idx
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speech_list.append(speech_i)
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speech_lengths_list.append(speech_lengths_i)
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feats_pad = pad_sequence(speech_list, batch_first=True, padding_value=0.0)
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speech_lengths_pad = torch.Tensor(speech_lengths_list).int()
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return feats_pad, speech_lengths_pad
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