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2332ba312d
* Begin to use multiple datasets. * Finish preparing training datasets. * Minor fixes * Copy files. * Finish training code. * Display losses for gigaspeech and librispeech separately. * Fix decode.py * Make the probability to select a batch from GigaSpeech configurable. * Update results. * Minor fixes.
76 lines
2.6 KiB
Python
76 lines
2.6 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 logging
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from pathlib import Path
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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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- cuts_XL_raw.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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f = self.manifest_dir / "cuts_XL_raw.jsonl.gz"
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logging.info(f"About to get train-XL cuts from {f}")
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return CutSet.from_jsonl_lazy(f)
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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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