icefall/egs/multi_zh-hans/ASR/local/compute_fbank_magicdata.py
zr_jin 0f1bc6f8af
Multi_zh-Hans Recipe (#1238)
* Init commit for recipes trained on multiple zh datasets.

* fbank extraction for thchs30

* added support for aishell1

* added support for aishell-2

* fixes

* fixes

* fixes

* added support for stcmds and primewords

* fixes

* added support for magicdata

script for fbank computation not done yet

* added script for magicdata fbank computation

* file permission fixed

* updated for the wenetspeech recipe

* updated

* Update preprocess_kespeech.py

* updated

* updated

* updated

* updated

* file permission fixed

* updated paths

* fixes

* added support for kespeech dev/test set fbank computation

* fixes for file permission

* refined support for KeSpeech

* added scripts for BPE model training

* updated

* init commit for the multi_zh-cn zipformer recipe

* disable speed perturbation by default

* updated

* updated

* added necessary files for the zipformer recipe

* removed redundant wenetspeech M and S sets

* updates for multi dataset decoding

* refined

* formatting issues fixed

* updated

* minor fixes

* this commit finalize the recipe (hopefully)

* fixed formatting issues

* minor fixes

* updated

* using soft links to reduce redundancy

* minor updates

* using soft links to reduce redundancy

* minor updates

* minor updates

* using soft links to reduce redundancy

* minor updates

* Update README.md

* minor updates

* Update egs/multi_zh-hans/ASR/local/compute_fbank_magicdata.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/compute_fbank_magicdata.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/compute_fbank_stcmds.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/compute_fbank_stcmds.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/compute_fbank_primewords.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/compute_fbank_primewords.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* minor updates

* minor fixes

* fixed a formatting issue

* Update preprocess_kespeech.py

* Update prepare.sh

* Update egs/multi_zh-hans/ASR/local/compute_fbank_kespeech_splits.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* Update egs/multi_zh-hans/ASR/local/preprocess_kespeech.py

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>

* removed redundant files

* symlinks added

* minor updates

* added CI tests for `multi_zh-hans`

* minor fixes

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

* Update run-multi-zh_hans-zipformer.sh

---------

Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>
2023-09-13 11:57:05 +08:00

123 lines
4.0 KiB
Python
Executable File

#!/usr/bin/env python3
# Copyright 2023 Xiaomi Corp. (authors: Fangjun Kuang
# Zengrui Jin)
#
# See ../../../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This file computes fbank features of the MagicData dataset.
It looks for manifests in the directory data/manifests/magicdata.
The generated fbank features are saved in data/fbank.
"""
import argparse
import logging
import os
from pathlib import Path
import torch
from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter
from lhotse.recipes.utils import read_manifests_if_cached
from icefall.utils import get_executor
# Torch's multithreaded behavior needs to be disabled or
# it wastes a lot of CPU and slow things down.
# Do this outside of main() in case it needs to take effect
# even when we are not invoking the main (e.g. when spawning subprocesses).
torch.set_num_threads(1)
torch.set_num_interop_threads(1)
def compute_fbank_magicdata(num_mel_bins: int = 80, speed_perturb: bool = False):
src_dir = Path("data/manifests/magicdata")
output_dir = Path("data/fbank")
num_jobs = min(30, os.cpu_count())
dataset_parts = ("train", "test", "dev")
prefix = "magicdata"
suffix = "jsonl.gz"
manifests = read_manifests_if_cached(
dataset_parts=dataset_parts,
output_dir=src_dir,
prefix=prefix,
suffix=suffix,
)
assert manifests is not None
assert len(manifests) == len(dataset_parts), (
len(manifests),
len(dataset_parts),
list(manifests.keys()),
dataset_parts,
)
extractor = Fbank(FbankConfig(num_mel_bins=num_mel_bins))
with get_executor() as ex: # Initialize the executor only once.
for partition, m in manifests.items():
if (output_dir / f"{prefix}_cuts_{partition}.{suffix}").is_file():
logging.info(f"{partition} already exists - skipping.")
continue
logging.info(f"Processing {partition}")
cut_set = CutSet.from_manifests(
recordings=m["recordings"],
supervisions=m["supervisions"],
)
if "train" in partition and speed_perturb:
cut_set = (
cut_set + cut_set.perturb_speed(0.9) + cut_set.perturb_speed(1.1)
)
cut_set = cut_set.compute_and_store_features(
extractor=extractor,
storage_path=f"{output_dir}/{prefix}_feats_{partition}",
# when an executor is specified, make more partitions
num_jobs=num_jobs if ex is None else 80,
executor=ex,
storage_type=LilcomChunkyWriter,
)
cut_set.to_file(output_dir / f"{prefix}_cuts_{partition}.{suffix}")
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--num-mel-bins",
type=int,
default=80,
help="""The number of mel bins for Fbank""",
)
parser.add_argument(
"--speed-perturb",
type=bool,
default=False,
help="Enable 0.9 and 1.1 speed perturbation for data augmentation. Default: False.",
)
return parser.parse_args()
if __name__ == "__main__":
formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
logging.basicConfig(format=formatter, level=logging.INFO)
args = get_args()
compute_fbank_magicdata(
num_mel_bins=args.num_mel_bins, speed_perturb=args.speed_perturb
)