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81 lines
2.6 KiB
Python
Executable File
81 lines
2.6 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2023 Xiaomi Corp. (authors: Zengwei Yao)
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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 split the LJSpeech dataset cuts into three sets:
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- training, 12500
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- validation, 100
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- test, 500
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The numbers are from https://arxiv.org/pdf/2106.06103.pdf
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Usage example:
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python3 ./local/split_subsets.py ./data/spectrogram
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"""
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import argparse
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import logging
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import random
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from pathlib import Path
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from lhotse import 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_dir",
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type=Path,
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default=Path("data/spectrogram"),
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help="Path to the manifest file",
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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_dir = Path(args.manifest_dir)
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prefix = "ljspeech"
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suffix = "jsonl.gz"
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# all_cuts = load_manifest_lazy(manifest_dir / f"{prefix}_cuts_all.{suffix}")
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all_cuts = load_manifest_lazy(manifest_dir / f"{prefix}_cuts_all_phonemized.{suffix}")
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cut_ids = list(all_cuts.ids)
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random.shuffle(cut_ids)
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train_cuts = all_cuts.subset(cut_ids=cut_ids[:12500])
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valid_cuts = all_cuts.subset(cut_ids=cut_ids[12500:12500 + 100])
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test_cuts = all_cuts.subset(cut_ids=cut_ids[12500 + 100:])
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assert len(train_cuts) == 12500, "expected 12500 cuts for training but got len(train_cuts)"
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assert len(valid_cuts) == 100, "expected 100 cuts but for validation but got len(valid_cuts)"
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assert len(test_cuts) == 500, "expected 500 cuts for test but got len(test_cuts)"
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train_cuts.to_file(manifest_dir / f"{prefix}_cuts_train.{suffix}")
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valid_cuts.to_file(manifest_dir / f"{prefix}_cuts_valid.{suffix}")
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test_cuts.to_file(manifest_dir / f"{prefix}_cuts_test.{suffix}")
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logging.info("Splitted into three sets: training (12500), validation (100), and test (500)")
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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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