diff --git a/src/llamafactory/data/mm_plugin.py b/src/llamafactory/data/mm_plugin.py
index fca092cb8..430fa885b 100644
--- a/src/llamafactory/data/mm_plugin.py
+++ b/src/llamafactory/data/mm_plugin.py
@@ -161,7 +161,9 @@ class MMPluginMixin:
         video_processor: BaseImageProcessor = getattr(
             processor, "video_processor", getattr(processor, "image_processor", None)
         )
-        feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None)
+        feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None) or getattr(
+            processor, "audio_processor", None
+        )
         if len(images) != 0 and self.image_token is None:
             raise ValueError(
                 "This model does not support image input. Please check whether the correct `template` is used."
@@ -390,7 +392,9 @@ class MMPluginMixin:
                 mm_inputs.update(video_processor(videos, return_tensors="pt"))
 
         if len(audios) != 0:
-            feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None)
+            feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None) or getattr(
+                processor, "audio_processor", None
+            )
             audios = self._regularize_audios(
                 audios,
                 sampling_rate=getattr(processor, "audio_sampling_rate", 16000),
@@ -1876,7 +1880,9 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
     ) -> dict[str, "torch.Tensor"]:
         image_processor: BaseImageProcessor = getattr(processor, "image_processor", None)
         video_processor: BaseVideoProcessor = getattr(processor, "video_processor", None)
-        feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None)
+        feature_extractor: SequenceFeatureExtractor = getattr(processor, "feature_extractor", None) or getattr(
+            processor, "audio_processor", None
+        )
         mm_inputs = {}
         if len(images) != 0:
             images = self._regularize_images(