update

egs/bengaliai_speech/ASR/local/compute_fbank_bengaliai_speech_splits.py

@@ -0,0 +1,152 @@
+#!/usr/bin/env python3
+# Copyright    2023  Xiaomi Corp.             (Yifan 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.
+
+import argparse
+import logging
+from datetime import datetime
+from pathlib import Path
+
+import torch
+from lhotse import (
+    CutSet,
+    KaldifeatFbank,
+    KaldifeatFbankConfig,
+    LilcomChunkyWriter,
+    set_audio_duration_mismatch_tolerance,
+    set_caching_enabled,
+)
+
+# 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(
+        "--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(
+        "--num-splits",
+        type=int,
+        required=True,
+        help="The number of splits of the train 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).",
+    )
+
+    return parser.parse_args()
+
+
+def compute_fbank_bengaliai_speech_splits(args):
+    num_splits = args.num_splits
+    output_dir = f"data/fbank/bengaliai_speech_train_split"
+    output_dir = Path(output_dir)
+    assert output_dir.exists(), f"{output_dir} does not exist!"
+
+    num_digits = 8
+
+    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}")
+
+    set_audio_duration_mismatch_tolerance(0.01)  # 10ms tolerance
+    set_caching_enabled(False)
+
+    for i in range(start, stop):
+        idx = f"{i + 1}".zfill(num_digits)
+        logging.info(f"Processing train split: {idx}")
+
+        cuts_path = output_dir / f"bengaliai_speech_cuts_train.{idx}.jsonl.gz"
+        if cuts_path.is_file():
+            logging.info(f"{cuts_path} exists - skipping")
+            continue
+
+        raw_cuts_path = (
+            output_dir / f"bengaliai_speech_cuts_train_raw.{idx}.jsonl.gz"
+        )
+
+        logging.info(f"Loading {raw_cuts_path}")
+        cut_set = CutSet.from_file(raw_cuts_path)
+
+        logging.info("Splitting cuts into smaller chunks.")
+        cut_set = cut_set.trim_to_supervisions(
+            keep_overlapping=False, min_duration=None
+        )
+
+        logging.info("Computing features")
+        cut_set = cut_set.compute_and_store_features_batch(
+            extractor=extractor,
+            storage_path=f"{output_dir}/bengaliai_speech_feats_train_{idx}",
+            num_workers=args.num_workers,
+            batch_duration=args.batch_duration,
+            storage_type=LilcomChunkyWriter,
+            overwrite=True,
+        )
+
+        logging.info(f"Saving to {cuts_path}")
+        cut_set.to_file(cuts_path)
+
+
+def 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_bengaliai_speech_splits(args)
+
+
+if __name__ == "__main__":
+    main()

egs/bengaliai_speech/ASR/local/compute_fbank_bengaliai_speech_valid_test.py

@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+# Copyright    2023  Xiaomi Corp.        (authors: Yifan 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 Bengali.AI Speech 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 torch
+from lhotse import CutSet, KaldifeatFbank, KaldifeatFbankConfig, LilcomChunkyWriter
+
+# 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_bengaliai_speech_valid_test():
+    src_dir = Path(f"data/manifests")
+    output_dir = Path(f"data/fbank")
+    num_workers = 42
+    batch_duration = 600
+
+    subsets = ("valid", "test")
+
+    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 partition in subsets:
+        cuts_path = output_dir / f"bengaliai_speech_cuts_{partition}.jsonl.gz"
+        if cuts_path.is_file():
+            logging.info(f"{partition} already exists - skipping.")
+            continue
+
+        raw_cuts_path = output_dir / f"bengaliai_speech_cuts_{partition}_raw.jsonl.gz"
+
+        logging.info(f"Loading {raw_cuts_path}")
+        cut_set = CutSet.from_file(raw_cuts_path)
+
+        logging.info("Splitting cuts into smaller chunks")
+        cut_set = cut_set.trim_to_supervisions(
+            keep_overlapping=False, min_duration=None
+        )
+
+        logging.info("Computing features")
+        cut_set = cut_set.compute_and_store_features_batch(
+            extractor=extractor,
+            storage_path=f"{output_dir}/bengaliai_speech_feats_{partition}",
+            num_workers=num_workers,
+            batch_duration=batch_duration,
+            storage_type=LilcomChunkyWriter,
+            overwrite=True,
+        )
+
+        logging.info(f"Saving to {cuts_path}")
+        cut_set.to_file(cuts_path)
+
+
+if __name__ == "__main__":
+    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
+
+    logging.basicConfig(format=formatter, level=logging.INFO)
+    compute_fbank_bengaliai_speech_valid_test()

egs/bengaliai_speech/ASR/prepare.sh

@@ -135,7 +135,7 @@ if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
       --num-workers $nj \
       --batch-duration 600 \
       --start 0 \
-      --num-splits 2000
+      --num-splits 300
     touch data/fbank/.bengaliai_speech_train.done
   fi
 fi
@@ -159,10 +159,8 @@ if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
     if [ ! -f $lang_dir/transcript_words.txt ]; then
       log "Generate data for BPE training"
       file=$(
-        find "data/fbank/bengaliai_speech_cuts_dirty_raw.jsonl.gz"
-	find "data/fbank/bengaliai_speech_cuts_dirty_sa_raw.jsonl.gz"
-	find "data/fbank/bengaliai_speech_cuts_clean_raw.jsonl.gz"
-	find "data/fbank/bengaliai_speech_cuts_clean_sa_raw.jsonl.gz"
+        find "data/fbank/bengaliai_speech_cuts_train_raw.jsonl.gz"
+	find "data/fbank/bengaliai_speech_cuts_valid_raw.jsonl.gz"
       )
       gunzip -c ${file} | awk -F '"' '{print $30}' > $lang_dir/transcript_words.txt