| | |
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| | | import copy |
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| | | |
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| | | import numpy as np |
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| | | from typeguard import check_argument_types |
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| | | import kaldi_native_fbank as knf |
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| | | |
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| | | root_dir = Path(__file__).resolve().parent |
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| | |
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| | | dither: float = 1.0, |
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| | | **kwargs, |
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| | | ) -> None: |
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| | | check_argument_types() |
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| | | |
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| | | opts = knf.FbankOptions() |
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| | | opts.frame_opts.samp_freq = fs |
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| | |
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| | | frame_num = self.compute_frame_num(input.shape[-1], self.frame_sample_length, self.frame_shift_sample_length) |
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| | | # update self.in_cache |
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| | | self.input_cache = input[:, -(input.shape[-1] - frame_num * self.frame_shift_sample_length):] |
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| | | waveforms = np.empty(0, dtype=np.int16) |
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| | | waveforms = np.empty(0, dtype=np.float32) |
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| | | feats_pad = np.empty(0, dtype=np.float32) |
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| | | feats_lens = np.empty(0, dtype=np.int32) |
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| | | if frame_num: |
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| | |
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| | | mat[i, :] = self.fbank_fn.get_frame(i) |
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| | | feat = mat.astype(np.float32) |
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| | | feat_len = np.array(mat.shape[0]).astype(np.int32) |
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| | | feats.append(mat) |
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| | | feats.append(feat) |
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| | | feats_lens.append(feat_len) |
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| | | |
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| | | waveforms = np.stack(waveforms) |
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