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remove ineffective normalize_text_alimeeting

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yfyeung 2025-04-29 10:28:01 -07:00 committed by Your Name
parent 26aef4a926
commit d1c336f589
1 changed files with 1 additions and 44 deletions
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45
egs/speech_llm/ASR_LLM/whisper_llm_zh/train.py
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@ -68,12 +68,7 @@ from whisper_encoder_forward_monkey_patch import replace_whisper_encoder_forward
from icefall.dist import get_rank, get_world_size
from icefall.env import get_env_info
from icefall.utils import (
AttributeDict,
MetricsTracker,
setup_logger,
str2bool,
)
from icefall.utils import AttributeDict, MetricsTracker, setup_logger, str2bool
DEFAULT_SPEECH_TOKEN = "<speech>"
@ -331,42 +326,6 @@ def compute_loss(
return input_ids, attention_mask, target_ids
def normalize_text_alimeeting(text: str, normalize: str = "m2met") -> str:
"""
Text normalization similar to M2MeT challenge baseline.
See: https://github.com/yufan-aslp/AliMeeting/blob/main/asr/local/text_normalize.pl
"""
if normalize == "none":
return text
elif normalize == "m2met":
import re
text = text.replace(" ", "")
text = text.replace("<sil>", "")
text = text.replace("<%>", "")
text = text.replace("<->", "")
text = text.replace("<$>", "")
text = text.replace("<#>", "")
text = text.replace("<_>", "")
text = text.replace("<space>", "")
text = text.replace("`", "")
text = text.replace("&", "")
text = text.replace(",", "")
if re.search("[a-zA-Z]", text):
text = text.upper()
text = text.replace("Ａ", "A")
text = text.replace("ａ", "A")
text = text.replace("ｂ", "B")
text = text.replace("ｃ", "C")
text = text.replace("ｋ", "K")
text = text.replace("ｔ", "T")
text = text.replace("，", "")
text = text.replace("丶", "")
text = text.replace("。", "")
text = text.replace("、", "")
text = text.replace("？", "")
return text
device = next(model.parameters()).device
feature = batch["inputs"]
@ -377,8 +336,6 @@ def compute_loss(
batch_idx_train = params.batch_idx_train
supervisions = batch["supervisions"]
texts = batch["supervisions"]["text"]
# remove spaces in texts
texts = [normalize_text_alimeeting(text) for text in texts]
messages = []
for i, text in enumerate(texts):