#!/usr/bin/env python3
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import sys
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try:
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import kaldifeat
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except:
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print("Please install kaldifeat first")
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sys.exit(0)
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import kaldi_native_fbank as knf
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import torch
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def main():
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sampling_rate = 16000
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samples = torch.randn(16000 * 10)
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opts = kaldifeat.FbankOptions()
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opts.frame_opts.dither = 0
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opts.mel_opts.num_bins = 80
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opts.frame_opts.snip_edges = False
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opts.mel_opts.debug_mel = False
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online_fbank = kaldifeat.OnlineFbank(opts)
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online_fbank.accept_waveform(sampling_rate, samples)
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opts = knf.FbankOptions()
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opts.frame_opts.dither = 0
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opts.mel_opts.num_bins = 80
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opts.frame_opts.snip_edges = False
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opts.mel_opts.debug_mel = False
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fbank = knf.OnlineFbank(opts)
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fbank.accept_waveform(sampling_rate, samples.tolist())
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assert online_fbank.num_frames_ready == fbank.num_frames_ready
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for i in range(fbank.num_frames_ready):
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f1 = online_fbank.get_frame(i)
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f2 = torch.from_numpy(fbank.get_frame(i))
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assert torch.allclose(f1, f2, atol=1e-3), (i, (f1 - f2).abs().max())
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if __name__ == "__main__":
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torch.manual_seed(20220825)
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main()
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print("success")
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