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50d2281524
* Add modified transducer for aishell. * Minor fixes. * Add extra data in transducer training. The extra data is from http://www.openslr.org/62/ * Update export.py and pretrained.py * Update CI to install pretrained models with aishell. * Update results. * Update results. * Update README. * Use symlinks to avoid copies.
54 lines
1.8 KiB
Python
54 lines
1.8 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 AIDatatang200zh:
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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_dev_raw.jsonl.gz
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- cuts_train_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_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_train_raw.jsonl.gz"
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logging.info(f"About to get train cuts from {f}")
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cuts_train = load_manifest(f)
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return cuts_train
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def valid_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_valid_raw.jsonl.gz"
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logging.info(f"About to get valid cuts from {f}")
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cuts_valid = load_manifest(f)
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return cuts_valid
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def test_cuts(self) -> CutSet:
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f = self.manifest_dir / "cuts_test_raw.jsonl.gz"
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logging.info(f"About to get test cuts from {f}")
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cuts_test = load_manifest(f)
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return cuts_test
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