speech_recognition/FunASR
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Merge pull request #169 from alibaba-damo-academy/dev_lhn

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update large dataset for sampling rate
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zhifu gao 2023-03-01 17:43:38 +08:00 committed by GitHub
commit 45dc9e484f
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3 changed files with 15 additions and 5 deletions
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5
funasr/datasets/large_datasets/build_dataloader.py
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@ -34,7 +34,7 @@ def load_seg_dict(seg_dict_file):
return seg_dict
class ArkDataLoader(AbsIterFactory):
def __init__(self, data_list, dict_file, dataset_conf, seg_dict_file=None, punc_dict_file=None, mode="train"):
def __init__(self, data_list, dict_file, dataset_conf, frontend_conf=None, seg_dict_file=None, punc_dict_file=None, mode="train"):
symbol_table = read_symbol_table(dict_file) if dict_file is not None else None
if seg_dict_file is not None:
seg_dict = load_seg_dict(seg_dict_file)
@ -45,10 +45,11 @@ class ArkDataLoader(AbsIterFactory):
else:
punc_dict = None
self.dataset_conf = dataset_conf
self.frontend_conf = frontend_conf
logging.info("dataloader config: {}".format(self.dataset_conf))
batch_mode = self.dataset_conf.get("batch_mode", "padding")
self.dataset = Dataset(data_list, symbol_table, seg_dict, punc_dict,
self.dataset_conf, mode=mode, batch_mode=batch_mode)
self.dataset_conf, self.frontend_conf, mode=mode, batch_mode=batch_mode)
def build_iter(self, epoch, shuffle=True):
self.dataset.set_epoch(epoch)

11
funasr/datasets/large_datasets/dataset.py
View File

@ -28,10 +28,11 @@ def read_lists(list_file):
class AudioDataset(IterableDataset):
def __init__(self, scp_lists, data_names, data_types, shuffle=True, mode="train"):
def __init__(self, scp_lists, data_names, data_types, frontend_conf=None, shuffle=True, mode="train"):
self.scp_lists = scp_lists
self.data_names = data_names
self.data_types = data_types
self.frontend_conf = frontend_conf
self.shuffle = shuffle
self.mode = mode
self.epoch = -1
@ -119,6 +120,11 @@ class AudioDataset(IterableDataset):
elif data_type == "sound":
key, path = item.strip().split()
waveform, sampling_rate = torchaudio.load(path)
if self.frontend_conf is not None:
if sampling_rate != self.frontend_conf["fs"]:
waveform = torchaudio.transforms.Resample(orig_freq=sampling_rate,
new_freq=self.frontend_conf["fs"])(waveform)
sampling_rate = self.frontend_conf["fs"]
waveform = waveform.numpy()
mat = waveform[0]
sample_dict[data_name] = mat
@ -153,13 +159,14 @@ def Dataset(data_list_file,
seg_dict,
punc_dict,
conf,
frontend_conf,
mode="train",
batch_mode="padding"):
scp_lists = read_lists(data_list_file)
shuffle = conf.get('shuffle', True)
data_names = conf.get("data_names", "speech,text")
data_types = conf.get("data_types", "kaldi_ark,text")
dataset = AudioDataset(scp_lists, data_names, data_types, shuffle=shuffle, mode=mode)
dataset = AudioDataset(scp_lists, data_names, data_types, frontend_conf=frontend_conf, shuffle=shuffle, mode=mode)
filter_conf = conf.get('filter_conf', {})
filter_fn = partial(filter, **filter_conf)

4
funasr/tasks/abs_task.py
View File

@ -1348,11 +1348,13 @@ class AbsTask(ABC):
if args.dataset_type == "large":
from funasr.datasets.large_datasets.build_dataloader import ArkDataLoader
train_iter_factory = ArkDataLoader(args.train_data_file, args.token_list, args.dataset_conf,
frontend_conf=args.frontend_conf if hasattr(args, "frontend_conf") else None,
seg_dict_file=args.seg_dict_file if hasattr(args,
"seg_dict_file") else None,
punc_dict_file=args.punc_list if hasattr(args, "punc_list") else None,
mode="train")
valid_iter_factory = ArkDataLoader(args.valid_data_file, args.token_list, args.dataset_conf,
valid_iter_factory = ArkDataLoader(args.valid_data_file, args.token_list, args.dataset_conf,
frontend_conf=args.frontend_conf if hasattr(args, "frontend_conf") else None,
seg_dict_file=args.seg_dict_file if hasattr(args,
"seg_dict_file") else None,
punc_dict_file=args.punc_list if hasattr(args, "punc_list") else None,