speech_recognition/FunASR
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Merge pull request #64 from alibaba-damo-academy/dev_lhn

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Dev lhn
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hnluo 2023-02-06 17:08:01 +08:00 committed by GitHub
commit 4f5b9354d0
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2 changed files with 18 additions and 4 deletions
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12
funasr/datasets/iterable_dataset.py
View File

@ -20,7 +20,7 @@ import os.path
from funasr.datasets.dataset import ESPnetDataset
SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'm4a', 'ogg', 'opus', 'wav', 'wma']
SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'ogg', 'opus', 'wav', 'pcm']
def load_kaldi(input):
retval = kaldiio.load_mat(input)
@ -60,9 +60,14 @@ def load_bytes(input):
array = np.frombuffer((middle_data.astype(dtype) - offset) / abs_max, dtype=np.float32)
return array
def load_pcm(input):
with open(input,"rb") as f:
bytes = f.read()
return load_bytes(bytes)
DATA_TYPES = {
"sound": lambda x: torchaudio.load(x)[0][0].numpy(),
"pcm": load_pcm,
"kaldi_ark": load_kaldi,
"bytes": load_bytes,
"waveform": lambda x: x,
@ -219,6 +224,9 @@ class IterableESPnetDataset(IterableDataset):
if audio_type not in SUPPORT_AUDIO_TYPE_SETS:
raise NotImplementedError(
f'Not supported audio type: {audio_type}')
if audio_type == "pcm":
_type = "pcm"
func = DATA_TYPES[_type]
array = func(value)
if self.fs is not None and name == "speech":
@ -318,6 +326,8 @@ class IterableESPnetDataset(IterableDataset):
if audio_type not in SUPPORT_AUDIO_TYPE_SETS:
raise NotImplementedError(
f'Not supported audio type: {audio_type}')
if audio_type == "pcm":
_type = "pcm"
func = DATA_TYPES[_type]
# Load entry
array = func(value)

10
funasr/utils/asr_utils.py
View File

@ -18,7 +18,7 @@ end_color = '\033[0m'
global_asr_language = 'zh-cn'
SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'm4a', 'ogg', 'opus', 'wav', 'wma']
SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'ogg', 'opus', 'wav', 'pcm']
def get_version():
return float(pkg_resources.get_distribution('easyasr').version)
@ -128,7 +128,12 @@ def get_sr_from_bytes(wav: bytes):
def get_sr_from_wav(fname: str):
fs = None
if os.path.isfile(fname):
audio, fs = torchaudio.load(fname)
audio_type = os.path.basename(fname).split(".")[1].lower()
if audio_type in SUPPORT_AUDIO_TYPE_SETS:
if audio_type == "pcm":
fs = None
else:
audio, fs = torchaudio.load(fname)
return fs
elif os.path.isdir(fname):
dir_files = os.listdir(fname)
@ -347,4 +352,3 @@ def print_progress(percent):
percent = 1
res = int(50 * percent) * '#'
print('\r[%-50s] %d%%' % (res, int(100 * percent)), end='')