diff --git a/tools/asr/fasterwhisper_asr.py b/tools/asr/fasterwhisper_asr.py
index e570f174..27cabbc2 100644
--- a/tools/asr/fasterwhisper_asr.py
+++ b/tools/asr/fasterwhisper_asr.py
@@ -10,6 +10,7 @@ from faster_whisper import WhisperModel
 from tqdm import tqdm
 
 from tools.asr.config import check_fw_local_models
+from tools.my_utils import load_cudnn
 
 # fmt: off
 language_code_list = [
@@ -93,6 +94,8 @@ def execute_asr(input_folder, output_folder, model_size, language, precision):
     return output_file_path
 
 
+load_cudnn()
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument(
diff --git a/tools/my_utils.py b/tools/my_utils.py
index 44d326e1..21fd55f8 100644
--- a/tools/my_utils.py
+++ b/tools/my_utils.py
@@ -1,11 +1,17 @@
+import ctypes
+import glob
 import os
+import sys
 import traceback
+from pathlib import Path
+
 import ffmpeg
-import numpy as np
 import gradio as gr
-from tools.i18n.i18n import I18nAuto
+import numpy as np
 import pandas as pd
 
+from tools.i18n.i18n import I18nAuto
+
 i18n = I18nAuto(language=os.environ.get("language", "Auto"))
 
 
@@ -127,3 +133,40 @@ def check_details(path_list=None, is_train=False, is_dataset_processing=False):
             ...
         else:
             gr.Warning(i18n("缺少语义数据集"))
+
+
+def load_cudnn():
+    import torch
+
+    if not torch.cuda.is_available():
+        print("[INFO] CUDA is not available, skipping cuDNN setup.")
+        return
+
+    if sys.platform == "win32":
+        torch_lib_dir = Path(torch.__file__).parent / "lib"
+        if torch_lib_dir.exists():
+            os.add_dll_directory(str(torch_lib_dir))
+            print(f"[INFO] Added DLL directory: {torch_lib_dir}")
+        else:
+            print(f"[WARNING] Torch lib directory not found: {torch_lib_dir}")
+
+    elif sys.platform == "linux":
+        site_packages = Path(torch.__file__).resolve().parents[1]
+        cudnn_dir = site_packages / "nvidia" / "cudnn" / "lib"
+
+        if not cudnn_dir.exists():
+            print(f"[ERROR] cudnn dir not found: {cudnn_dir}")
+            return
+
+        pattern = str(cudnn_dir / "libcudnn_cnn*.so*")
+        matching_files = sorted(glob.glob(pattern))
+        if not matching_files:
+            print(f"[ERROR] No libcudnn_cnn*.so* found in {cudnn_dir}")
+            return
+
+        for so_path in matching_files:
+            try:
+                ctypes.CDLL(so_path, mode=ctypes.RTLD_GLOBAL)
+                print(f"[INFO] Loaded: {so_path}")
+            except OSError as e:
+                print(f"[WARNING] Failed to load {so_path}: {e}")