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Funasr1.0 (#1284)
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* funasr1.0 update

* funasr1.0 paraformer-en

* update with main (#1281)

* Funasr1.0 (#1279)

* funasr1.0 update

* funasr1.0 paraformer-en

* update speaker infer

* update device

* update device

* update raw_text

* update infer

* update

* update infer

* bug fix

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Co-authored-by: shixian.shi <[email protected]>
Co-authored-by: Shi Xian <[email protected]>

* punc bugfix

* reduce_channels

---------

Co-authored-by: shixian.shi <[email protected]>
Co-authored-by: Shi Xian <[email protected]>
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3 people authored Jan 23, 2024
1 parent d8ef0e9 commit 2c3183b
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3 changes: 2 additions & 1 deletion funasr/models/ct_transformer/model.py
Original file line number Diff line number Diff line change
Expand Up @@ -333,12 +333,13 @@ def inference(self,
elif new_mini_sentence[-1] == ",":
new_mini_sentence_out = new_mini_sentence[:-1] + "."
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [self.sentence_end_id]
elif new_mini_sentence[-1] != "。" and new_mini_sentence[-1] != "?" and len(new_mini_sentence[-1].encode())==0:
elif new_mini_sentence[-1] != "。" and new_mini_sentence[-1] != "?" and len(new_mini_sentence[-1].encode())!=1:
new_mini_sentence_out = new_mini_sentence + "。"
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [self.sentence_end_id]
elif new_mini_sentence[-1] != "." and new_mini_sentence[-1] != "?" and len(new_mini_sentence[-1].encode())==1:
new_mini_sentence_out = new_mini_sentence + "."
new_mini_sentence_punc_out = new_mini_sentence_punc[:-1] + [self.sentence_end_id]

# keep a punctuations array for punc segment
if punc_array is None:
punc_array = punctuations
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3 changes: 2 additions & 1 deletion funasr/utils/load_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,8 @@ def load_audio_text_image_video(data_or_path_or_list, fs: int = 16000, audio_fs:
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)
data_or_path_or_list = data_or_path_or_list[0, :]
if kwargs.get("reduce_channels", True):
data_or_path_or_list = data_or_path_or_list.mean(0)
elif data_type == "text" and tokenizer is not None:
data_or_path_or_list = tokenizer.encode(data_or_path_or_list)
elif data_type == "image": # undo
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