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ac84220de9
* Copy files for editing. * Use librispeech + gigaspeech with modified conformer. * Support specifying number of workers for on-the-fly feature extraction. * Feature extraction code for GigaSpeech. * Combine XL splits lazily during training. * Fix warnings in decoding. * Add decoding code for GigaSpeech. * Fix decoding the gigaspeech dataset. We have to use the decoder/joiner networks for the GigaSpeech dataset. * Disable speed perturbe for XL subset. * Compute the Nbest oracle WER for RNN-T decoding. * Minor fixes. * Minor fixes. * Add results. * Update results. * Update CI. * Update results. * Fix style issues. * Update results. * Fix style issues.
95 lines
3.1 KiB
Python
95 lines
3.1 KiB
Python
# Copyright 2021 Piotr Żelasko
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# 2022 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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import glob
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import logging
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import re
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from pathlib import Path
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import lhotse
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from lhotse import CutSet, load_manifest
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class GigaSpeech:
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def __init__(self, manifest_dir: str):
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"""
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Args:
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manifest_dir:
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It is expected to contain the following files::
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- XL_split_2000/cuts_XL.*.jsonl.gz
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- cuts_L_raw.jsonl.gz
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- cuts_M_raw.jsonl.gz
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- cuts_S_raw.jsonl.gz
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- cuts_XS_raw.jsonl.gz
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- cuts_DEV_raw.jsonl.gz
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- cuts_TEST_raw.jsonl.gz
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"""
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self.manifest_dir = Path(manifest_dir)
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def train_XL_cuts(self) -> CutSet:
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logging.info("About to get train-XL cuts")
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filenames = list(
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glob.glob(f"{self.manifest_dir}/XL_split_2000/cuts_XL.*.jsonl.gz")
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)
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pattern = re.compile(r"cuts_XL.([0-9]+).jsonl.gz")
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idx_filenames = [
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(int(pattern.search(f).group(1)), f) for f in filenames
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]
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idx_filenames = sorted(idx_filenames, key=lambda x: x[0])
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sorted_filenames = [f[1] for f in idx_filenames]
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logging.info(f"Loading {len(sorted_filenames)} splits")
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return lhotse.combine(
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lhotse.load_manifest_lazy(p) for p in sorted_filenames
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)
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def train_L_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_L_raw.jsonl.gz"
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logging.info(f"About to get train-L cuts from {f}")
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return CutSet.from_jsonl_lazy(f)
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def train_M_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_M_raw.jsonl.gz"
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logging.info(f"About to get train-M cuts from {f}")
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return CutSet.from_jsonl_lazy(f)
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def train_S_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_S_raw.jsonl.gz"
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logging.info(f"About to get train-S cuts from {f}")
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return CutSet.from_jsonl_lazy(f)
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def train_XS_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_XS_raw.jsonl.gz"
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logging.info(f"About to get train-XS cuts from {f}")
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return CutSet.from_jsonl_lazy(f)
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def test_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_TEST.jsonl.gz"
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logging.info(f"About to get TEST cuts from {f}")
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return load_manifest(f)
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def dev_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_DEV.jsonl.gz"
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logging.info(f"About to get DEV cuts from {f}")
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return load_manifest(f)
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