Recipe for Multi-lingual LibriSpeech

egs/mls/ASR/local/compute_fbank_mls.py

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+#!/usr/bin/env python3
+# Copyright    2024  Xiaomi Corp.        (authors: Xiaoyu Yang)
+#
+# 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 LibriSpeech dataset.
+It looks for manifests in the directory data/manifests.
+
+The generated fbank features are saved in data/fbank.
+"""
+
+import argparse
+import logging
+import os
+from pathlib import Path
+from typing import Optional
+
+import sentencepiece as spm
+import torch
+from filter_cuts import filter_cuts
+from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter
+from lhotse.recipes.utils import read_manifests_if_cached
+
+from icefall.utils import get_executor, str2bool
+
+# 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 get_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--manifest-dir",
+        type=str,
+        default="data/manifests",
+    )
+
+    parser.add_argument(
+        "--fbank-dir",
+        type=str,
+        default="data/fbank_mls",
+    )
+
+    parser.add_argument(
+        "--part",
+        type=str,
+        help="Which language to prepare, if all, prepare all languages",
+        choices=["english", "dutch", "german", "spanish", "french", "italian", "polish", "portuguese", "all"]
+    )
+
+    return parser.parse_args()
+
+def compute_fbank_mls(
+    manifest_dir=str,
+    fbank_dir=str,
+    part=str,
+):
+    src_dir = Path("data/manifests")
+    output_dir = Path(fbank_dir)
+    num_jobs = min(15, os.cpu_count())
+    num_mel_bins = 80
+
+    if part == "all":
+        dataset_parts = [
+            "english",
+            "dutch",
+            "german",
+            "spanish"
+        ]
+    else:
+        dataset_parts = [part]
+    splits = ["train", "test", "dev"]
+
+    num_jobs = 15
+    num_mel_bins = 80
+    extractor = Fbank(FbankConfig(num_mel_bins=num_mel_bins))
+
+    for language in dataset_parts:
+        for split in splits:
+            recording_file = src_dir / f"mls-{language}_recordings_{split}.jsonl.gz"
+            supervision_file = src_dir / f"mls-{language}_supervisions_{split}.jsonl.gz"
+            recordings = CutSet.from_file(recording_file)
+            supervisions = CutSet.from_file(supervision_file)
+
+            cut_set = CutSet.from_manifests(
+                recordings=recordings,
+                supervisions=supervisions,
+            )
+
+            prefix = f"mls-{language}"
+            with get_executor() as ex:
+                cut_set = cut_set.compute_and_store_features(
+                    extractor=extractor,
+                    storage_path=f"{output_dir}/{prefix}_feats_{split}",
+                    # when an executor is specified, make more partitions
+                    num_jobs=num_jobs if ex is None else 80,
+                    executor=ex,
+                    storage_type=LilcomChunkyWriter,
+                )
+
+            cuts_filename = output_dir / f"mls-{language}_{split}.jsonl.gz"
+
+            logging.info(f"Saving to {cuts_filename}")
+            cut_set.to_file(cuts_filename)
+
+
+if __name__ == "__main__":
+    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
+
+    logging.basicConfig(format=formatter, level=logging.INFO)
+    args = get_args()
+    logging.info(vars(args))
+    compute_fbank_mls(
+        manifest_dir=args.manifest_dir,
+        fbank_dir=args.fbank_dir,
+        part=args.part,
+    )
+
+

egs/mls/ASR/local/compute_fbank_mls_splits.py

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+#!/usr/bin/env python3
+# Copyright    2021  Johns Hopkins University (Piotr Żelasko)
+# Copyright    2021  Xiaomi Corp.             (Fangjun Kuang)
+#
+# 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.
+
+import argparse
+import logging
+from datetime import datetime
+from pathlib import Path
+
+import torch
+from lhotse import CutSet, KaldifeatFbank, KaldifeatFbankConfig
+
+# 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 get_parser():
+    parser = argparse.ArgumentParser(
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter
+    )
+
+    parser.add_argument(
+        "--num-workers",
+        type=int,
+        default=20,
+        help="Number of dataloading workers used for reading the audio.",
+    )
+    parser.add_argument(
+        "--batch-duration",
+        type=float,
+        default=600.0,
+        help="The maximum number of audio seconds in a batch."
+        "Determines batch size dynamically.",
+    )
+
+    parser.add_argument(
+        "--language",
+        type=str,
+        default="english",
+    )
+
+    parser.add_argument(
+        "--num-splits",
+        type=int,
+        required=True,
+        help="The number of splits of the English subset",
+    )
+
+    parser.add_argument(
+        "--start",
+        type=int,
+        default=0,
+        help="Process pieces starting from this number (inclusive).",
+    )
+
+    parser.add_argument(
+        "--stop",
+        type=int,
+        default=-1,
+        help="Stop processing pieces until this number (exclusive).",
+    )
+
+    parser.add_argument(
+        "--fbank-dir",
+        type=str,
+        default="data/fbank_mls"
+    )
+    return parser
+
+
+def compute_fbank_mls_splits(args):
+    num_splits = args.num_splits
+    output_dir = f"{args.fbank_dir}/{args.language}_split"
+    output_dir = Path(output_dir)
+    assert output_dir.exists(), f"{output_dir} does not exist!"
+
+    num_digits = 8  # num_digits is fixed by lhotse split-lazy
+
+    start = args.start
+    stop = args.stop
+    if stop < start:
+        stop = num_splits
+
+    stop = min(stop, num_splits)
+
+    device = torch.device("cpu")
+    if torch.cuda.is_available():
+        device = torch.device("cuda", 0)
+    extractor = KaldifeatFbank(KaldifeatFbankConfig(device=device))
+    logging.info(f"device: {device}")
+
+    for i in range(start, stop):
+        idx = f"{i}".zfill(num_digits)
+        logging.info(f"Processing {idx}/{num_splits}")
+
+        cuts_path = output_dir / f"mls-{args.language}_train.{idx}.jsonl.gz"
+        if cuts_path.is_file():
+            logging.info(f"{cuts_path} exists - skipping")
+            continue
+
+        raw_cuts_path = output_dir / f"mls-{args.language}_train_raw.{idx}.jsonl.gz"
+
+        logging.info(f"Loading {raw_cuts_path}")
+        cut_set = CutSet.from_file(raw_cuts_path)
+
+        logging.info("Computing features")
+
+        cut_set = cut_set.compute_and_store_features_batch(
+            extractor=extractor,
+            storage_path=f"{output_dir}/feats_{args.language}_{idx}",
+            num_workers=args.num_workers,
+            batch_duration=args.batch_duration,
+            overwrite=True,
+        )
+
+        logging.info("About to split cuts into smaller chunks.")
+        cut_set = cut_set.trim_to_supervisions(
+            keep_overlapping=False, min_duration=None
+        )
+
+        logging.info(f"Saving to {cuts_path}")
+        cut_set.to_file(cuts_path)
+        logging.info(f"Saved to {cuts_path}")
+
+
+def main():
+    now = datetime.now()
+    date_time = now.strftime("%Y-%m-%d-%H-%M-%S")
+
+    log_filename = "log-compute_fbank_mls_splits"
+    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
+    log_filename = f"{log_filename}-{date_time}"
+
+    logging.basicConfig(
+        filename=log_filename,
+        format=formatter,
+        level=logging.INFO,
+        filemode="w",
+    )
+
+    console = logging.StreamHandler()
+    console.setLevel(logging.INFO)
+    console.setFormatter(logging.Formatter(formatter))
+    logging.getLogger("").addHandler(console)
+
+    parser = get_parser()
+    args = parser.parse_args()
+    logging.info(vars(args))
+
+    compute_fbank_mls_splits(args)
+
+
+if __name__ == "__main__":
+    main()