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Add finetune resampling function under small data type.

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zhuyunfeng 2023-03-11 13:23:34 +08:00
parent 716ea81703
commit 4afdd97df4
3 changed files with 16 additions and 6 deletions
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10
funasr/datasets/dataset.py
View File

@ -107,7 +107,7 @@ class H5FileWrapper:
return value[()] return value[()]
def sound_loader(path, float_dtype=None): def sound_loader(path, dest_sample_rate=16000, float_dtype=None):
# The file is as follows: # The file is as follows:
# utterance_id_A /some/where/a.wav # utterance_id_A /some/where/a.wav
# utterance_id_B /some/where/a.flac # utterance_id_B /some/where/a.flac
@ -115,7 +115,7 @@ def sound_loader(path, float_dtype=None):
# NOTE(kamo): SoundScpReader doesn't support pipe-fashion # NOTE(kamo): SoundScpReader doesn't support pipe-fashion
# like Kaldi e.g. "cat a.wav |". # like Kaldi e.g. "cat a.wav |".
# NOTE(kamo): The audio signal is normalized to [-1,1] range. # NOTE(kamo): The audio signal is normalized to [-1,1] range.
loader = SoundScpReader(path, normalize=True, always_2d=False) loader = SoundScpReader(path, dest_sample_rate=16000, normalize=True, always_2d=False)
# SoundScpReader.__getitem__() returns Tuple[int, ndarray], # SoundScpReader.__getitem__() returns Tuple[int, ndarray],
# but ndarray is desired, so Adapter class is inserted here # but ndarray is desired, so Adapter class is inserted here
@ -139,7 +139,7 @@ def rand_int_loader(filepath, loader_type):
DATA_TYPES = { DATA_TYPES = {
"sound": dict( "sound": dict(
func=sound_loader, func=sound_loader,
kwargs=["float_dtype"], kwargs=["dest_sample_rate","float_dtype"],
help="Audio format types which supported by sndfile wav, flac, etc." help="Audio format types which supported by sndfile wav, flac, etc."
"\n\n" "\n\n"
" utterance_id_a a.wav\n" " utterance_id_a a.wav\n"
@ -282,6 +282,7 @@ class ESPnetDataset(AbsDataset):
int_dtype: str = "long", int_dtype: str = "long",
max_cache_size: Union[float, int, str] = 0.0, max_cache_size: Union[float, int, str] = 0.0,
max_cache_fd: int = 0, max_cache_fd: int = 0,
dest_sample_rate: int = 16000,
): ):
assert check_argument_types() assert check_argument_types()
if len(path_name_type_list) == 0: if len(path_name_type_list) == 0:
@ -295,6 +296,7 @@ class ESPnetDataset(AbsDataset):
self.float_dtype = float_dtype self.float_dtype = float_dtype
self.int_dtype = int_dtype self.int_dtype = int_dtype
self.max_cache_fd = max_cache_fd self.max_cache_fd = max_cache_fd
self.dest_sample_rate = dest_sample_rate
self.loader_dict = {} self.loader_dict = {}
self.debug_info = {} self.debug_info = {}
@ -335,6 +337,8 @@ class ESPnetDataset(AbsDataset):
for key2 in dic["kwargs"]: for key2 in dic["kwargs"]:
if key2 == "loader_type": if key2 == "loader_type":
kwargs["loader_type"] = loader_type kwargs["loader_type"] = loader_type
elif key2 == "dest_sample_rate" and loader_type=="sound":
kwargs["dest_sample_rate"] = self.dest_sample_rate
elif key2 == "float_dtype": elif key2 == "float_dtype":
kwargs["float_dtype"] = self.float_dtype kwargs["float_dtype"] = self.float_dtype
elif key2 == "int_dtype": elif key2 == "int_dtype":

11
funasr/fileio/sound_scp.py
View File

@ -4,6 +4,7 @@ from typing import Union
import numpy as np import numpy as np
import soundfile import soundfile
import librosa
from typeguard import check_argument_types from typeguard import check_argument_types
from funasr.fileio.read_text import read_2column_text from funasr.fileio.read_text import read_2column_text
@ -30,6 +31,7 @@ class SoundScpReader(collections.abc.Mapping):
dtype=np.int16, dtype=np.int16,
always_2d: bool = False, always_2d: bool = False,
normalize: bool = False, normalize: bool = False,
dest_sample_rate: int = 16000,
): ):
assert check_argument_types() assert check_argument_types()
self.fname = fname self.fname = fname
@ -37,15 +39,18 @@ class SoundScpReader(collections.abc.Mapping):
self.always_2d = always_2d self.always_2d = always_2d
self.normalize = normalize self.normalize = normalize
self.data = read_2column_text(fname) self.data = read_2column_text(fname)
self.dest_sample_rate = dest_sample_rate
def __getitem__(self, key): def __getitem__(self, key):
wav = self.data[key] wav = self.data[key]
if self.normalize: if self.normalize:
# soundfile.read normalizes data to [-1,1] if dtype is not given # soundfile.read normalizes data to [-1,1] if dtype is not given
array, rate = soundfile.read(wav, always_2d=self.always_2d) array, rate = librosa.load(
wav, sr=self.dest_sample_rate, mono=not self.always_2d
)
else: else:
array, rate = soundfile.read( array, rate = librosa.load(
wav, dtype=self.dtype, always_2d=self.always_2d wav, sr=self.dest_sample_rate, mono=not self.always_2d, dtype=self.dtype
) )
return rate, array return rate, array

1
funasr/tasks/abs_task.py
View File

@ -1576,6 +1576,7 @@ class AbsTask(ABC):
preprocess=iter_options.preprocess_fn, preprocess=iter_options.preprocess_fn,
max_cache_size=iter_options.max_cache_size, max_cache_size=iter_options.max_cache_size,
max_cache_fd=iter_options.max_cache_fd, max_cache_fd=iter_options.max_cache_fd,
dest_sample_rate=args.frontend_conf["fs"],
) )
cls.check_task_requirements( cls.check_task_requirements(
dataset, args.allow_variable_data_keys, train=iter_options.train dataset, args.allow_variable_data_keys, train=iter_options.train