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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

---------

Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
Co-authored-by: Shi Xian <40013335+R1ckShi@users.noreply.github.com>

* punc bugfix

* reduce_channels

---------

Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
Co-authored-by: Shi Xian <40013335+R1ckShi@users.noreply.github.com>
This commit is contained in:
zhifu gao 2024-01-23 11:16:34 +08:00 committed by GitHub
parent d8ef0e9eb4
commit 2c3183b611
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2 changed files with 4 additions and 2 deletions
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3
funasr/models/ct_transformer/model.py
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@ -333,12 +333,13 @@ class CTTransformer(torch.nn.Module):
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

3
funasr/utils/load_utils.py
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@ -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