speech_recognition/FunASR
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语帆 2024-02-28 16:14:57 +08:00
parent a88b51c544
commit 31e2eb39ad
2 changed files with 4 additions and 4 deletions
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7
funasr/models/lcbnet/model.py
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@ -422,7 +422,6 @@ class LCBNet(nn.Module):
else:
# extract fbank feats
time1 = time.perf_counter()
pdb.set_trace()
sample_list = load_audio_text_image_video(data_in, fs=frontend.fs, audio_fs=kwargs.get("fs", 16000),
data_type=kwargs.get("data_type", "sound"),
tokenizer=tokenizer)
@ -443,9 +442,11 @@ class LCBNet(nn.Module):
encoder_out, encoder_out_lens = self.encode(speech, speech_lengths)
if isinstance(encoder_out, tuple):
encoder_out = encoder_out[0]
pdb.set_trace()
ocr = ocr_sample_list[0]
ocr_list_new = [[x + 1 if x != 0 else x for x in sublist] for sublist in ocr_sample_list]
ocr = torch.tensor(ocr_list_new)
ocr_lengths = ocr.new_full([1], dtype=torch.long, fill_value=ocr.size(1))
pdb.set_trace()
ocr, ocr_lens, _ = self.text_encoder(ocr, ocr_lengths)
pdb.set_trace()
# c. Passed the encoder result and the beam search

1
funasr/utils/load_utils.py
View File

@ -31,7 +31,6 @@ def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs:
return [load_audio_text_image_video(audio, fs=fs, audio_fs=audio_fs, data_type=data_type, **kwargs) for audio in data_or_path_or_list]
if isinstance(data_or_path_or_list, str) and data_or_path_or_list.startswith('http'): # download url to local file
data_or_path_or_list = download_from_url(data_or_path_or_list)
pdb.set_trace()
if isinstance(data_or_path_or_list, str) and os.path.exists(data_or_path_or_list): # local file
if data_type is None or data_type == "sound":
data_or_path_or_list, audio_fs = torchaudio.load(data_or_path_or_list)