Use default storage_type

egs/gigaspeech/ASR/local/compute_fbank_gigaspeech_dev_test.py

@@ -24,7 +24,6 @@ from lhotse import (
     CutSet,
     KaldifeatFbank,
     KaldifeatFbankConfig,
-    LilcomHdf5Writer,
 )
 
 # Torch's multithreaded behavior needs to be disabled or
@@ -70,7 +69,6 @@ def compute_fbank_gigaspeech_dev_test():
             storage_path=f"{in_out_dir}/feats_{partition}",
             num_workers=num_workers,
             batch_duration=batch_duration,
-            storage_type=LilcomHdf5Writer,
         )
         cut_set = cut_set.trim_to_supervisions(
             keep_overlapping=False, min_duration=None

egs/gigaspeech/ASR/local/compute_fbank_gigaspeech_splits.py

@@ -23,7 +23,6 @@ from pathlib import Path
 
 import torch
 from lhotse import (
-    ChunkedLilcomHdf5Writer,
     CutSet,
     KaldifeatFbank,
     KaldifeatFbankConfig,
@@ -124,7 +123,6 @@ def compute_fbank_gigaspeech_splits(args):
             storage_path=f"{output_dir}/feats_XL_{idx}",
             num_workers=args.num_workers,
             batch_duration=args.batch_duration,
-            storage_type=ChunkedLilcomHdf5Writer,
         )
 
         logging.info("About to split cuts into smaller chunks.")

egs/gigaspeech/ASR/local/compute_fbank_musan.py

@@ -24,7 +24,6 @@ from lhotse import (
     CutSet,
     KaldifeatFbank,
     KaldifeatFbankConfig,
-    LilcomHdf5Writer,
     combine,
 )
 from lhotse.recipes.utils import read_manifests_if_cached
@@ -86,7 +85,6 @@ def compute_fbank_musan():
             storage_path=f"{output_dir}/feats_musan",
             num_workers=num_workers,
             batch_duration=batch_duration,
-            storage_type=LilcomHdf5Writer,
         )
     )
     musan_cuts.to_json(musan_cuts_path)