mirror of
https://github.com/k2-fsa/icefall.git
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* add the `voxpopuli` recipe - this is the data preparation - there is no ASR training and no results * update the PR#1374 (feedback from @csukuangfj) - fixing .py headers and docstrings - removing BUT specific parts of `prepare.sh` - adding assert `num_jobs >= num_workers` to `compute_fbank.py` - narrowing list of languages (let's limit to ASR sets with transcripts for now) - added links to `README.md` - extending `text_from_manifest.py`
124 lines
3.8 KiB
Python
Executable File
124 lines
3.8 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2022 Xiaomi Corp. (authors: Fangjun Kuang)
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# 2023 Brno University of Technology (authors: Karel Veselý)
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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 checks the following assumptions of the generated manifest:
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- Single supervision per cut
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- Supervision time bounds are within Cut time bounds
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- Duration of Cut and Superivion are equal
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We will add more checks later if needed.
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Usage example:
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python3 ./local/validate_manifest.py \
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./data/fbank/librispeech_cuts_train-clean-100.jsonl.gz
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(Based on: `librispeech/ASR/local/validate_manifest.py`)
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"""
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import argparse
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import logging
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from pathlib import Path
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from lhotse import CutSet, load_manifest_lazy
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from lhotse.cut import Cut
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from lhotse.dataset.speech_recognition import validate_for_asr
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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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"cutset_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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return parser.parse_args()
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def validate_one_supervision_per_cut(c: Cut):
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if len(c.supervisions) != 1:
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raise ValueError(f"{c.id} has {len(c.supervisions)} supervisions")
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def validate_supervision_and_cut_time_bounds(c: Cut):
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tol = 2e-3 # same tolerance as in 'validate_for_asr()'
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s = c.supervisions[0]
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# Supervision start time is relative to Cut ...
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# https://lhotse.readthedocs.io/en/v0.10_e/cuts.html
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if s.start < -tol:
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raise ValueError(
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f"{c.id}: Supervision start time {s.start} must not be negative."
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)
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if s.start > tol:
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raise ValueError(
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f"{c.id}: Supervision start time {s.start} "
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"is not at the beginning of the Cut. "
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"Please apply `lhotse cut trim-to-supervisions`."
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)
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if c.start + s.end > c.end + tol:
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raise ValueError(
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f"{c.id}: Supervision end time {c.start+s.end} is larger "
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f"than cut end time {c.end}"
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)
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if s.duration != c.duration:
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raise ValueError(
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f"{c.id}: Cut duration {c.duration} and supervision duration "
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f"{s.duration} must be the same.\n"
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f"The difference causes problems in the training code : "
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f"+/- 1 frame in `x`, `x_lens` in `Zipformer::forward()`.\n"
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f"Did you forget to apply `trim_to_supervisions()` ?"
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)
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def main():
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args = get_args()
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manifest = args.cutset_manifest
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logging.info(f"Validating {manifest}")
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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)
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try:
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for c in cut_set:
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validate_one_supervision_per_cut(c)
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validate_supervision_and_cut_time_bounds(c)
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# Validation from K2 training
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# - checks supervision start is 0
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# - checks supervision.duration is not longer than cut.duration
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# - there is tolerance 2ms
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validate_for_asr(cut_set)
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except BaseException as e:
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logging.error(str(e))
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raise
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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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