mirror of
https://github.com/k2-fsa/icefall.git
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85 lines
2.2 KiB
Python
Executable File
85 lines
2.2 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2024 Xiaomi Corp. (authors: Fangjun Kuang)
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#
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# See ../../../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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This script compute the mean and std of the fbank features.
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"""
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import argparse
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import json
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import logging
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from pathlib import Path
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import torch
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from lhotse import CutSet, load_manifest_lazy
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"manifest",
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type=Path,
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help="Path to the manifest file",
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)
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parser.add_argument(
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"cmvn",
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type=Path,
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help="Path to the cmvn.json",
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)
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return parser.parse_args()
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def main():
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args = get_args()
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manifest = args.manifest
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logging.info(
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f"Computing fbank mean and std for {manifest} and saving to {args.cmvn}"
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)
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assert manifest.is_file(), f"{manifest} does not exist"
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cut_set = load_manifest_lazy(manifest)
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assert isinstance(cut_set, CutSet), type(cut_set)
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feat_dim = cut_set[0].features.num_features
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num_frames = 0
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s = 0
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sq = 0
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for c in cut_set:
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f = torch.from_numpy(c.load_features())
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num_frames += f.shape[0]
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s += f.sum()
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sq += f.square().sum()
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fbank_mean = s / (num_frames * feat_dim)
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fbank_var = sq / (num_frames * feat_dim) - fbank_mean * fbank_mean
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print("fbank var", fbank_var)
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fbank_std = fbank_var.sqrt()
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with open(args.cmvn, "w") as f:
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json.dump({"fbank_mean": fbank_mean.item(), "fbank_std": fbank_std.item()}, f)
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f.write("\n")
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if __name__ == "__main__":
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formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
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logging.basicConfig(format=formatter, level=logging.INFO)
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main()
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