mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-12-11 06:55:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

from local

Browse Source
This commit is contained in:
dohe0342 2023-06-09 17:26:50 +09:00
parent e10d68fa1e
commit cbe026f8ff
2 changed files with 3 additions and 40 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

BIN
egs/tedlium3/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp
View File

Binary file not shown.

43
egs/tedlium3/ASR/pruned_transducer_stateless_d2v_v2/decode.py
View File

@ -823,47 +823,10 @@ def main():
# we need cut ids to display recognition results.
args.return_cuts = True
librispeech = LibriSpeechAsrDataModule(args)
tedlium = TedLiumAsrDataModule(args)
test_cuts = tedlium.test_cuts()
test_dl = tedlium.train_dataloaders(train_cuts)
#test_clean_cuts = librispeech.test_clean_cuts(option='male')
#test_other_cuts = librispeech.test_other_cuts(option='male')
if 0:
test_clean_cuts = librispeech.test_clean_user(option=option)
test_other_cuts = librispeech.test_other_user(option=option)
test_clean_dl = librispeech.test_dataloaders(test_clean_cuts)
test_other_dl = librispeech.test_dataloaders(test_other_cuts)
test_sets = [f"test-clean", f"test-other"]
test_dl = [test_clean_dl, test_other_dl]
if 0:
option = 'big'
test_clean_cuts = librispeech.test_clean_user(option=option)
test_other_cuts = librispeech.test_other_user(option=option)
test_clean_dl = librispeech.test_dataloaders(test_clean_cuts)
test_other_dl = librispeech.test_dataloaders(test_other_cuts)
test_sets = [f"test-clean_sampling"]
test_dl = [test_clean_dl]
#test_sets = [f"test-other_sampling"]
#test_dl = [test_other_dl]
#test_sets = [f"test-clean_sampling", f"test-other_sampling"]
#test_dl = [test_clean_dl, test_other_dl]
if 0:
option = '6938'
test_clean_cuts = librispeech.vox_cuts(option=option)
test_clean_dl = librispeech.test_dataloaders(test_clean_cuts)
test_sets = [f"test-clean_sampling"]
test_dl = [test_clean_dl]
if 1:
test_clean_cuts = librispeech.userlibri_cuts(option=params.spk_id)
test_clean_dl = librispeech.test_dataloaders(test_clean_cuts)
test_sets = [f"{params.spk_id}"]
test_dl = [test_clean_dl]
for test_set, test_dl in zip(test_sets, test_dl):
results_dict = decode_dataset(
dl=test_dl,