diff --git a/funasr/datasets/iterable_dataset.py b/funasr/datasets/iterable_dataset.py
index 2ac37b2f9..fa0adeb28 100644
--- a/funasr/datasets/iterable_dataset.py
+++ b/funasr/datasets/iterable_dataset.py
@@ -20,7 +20,7 @@ import os.path
 from funasr.datasets.dataset import ESPnetDataset
 
 
-SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'm4a', 'ogg', 'opus', 'wav', 'wma']
+SUPPORT_AUDIO_TYPE_SETS = ['flac', 'mp3', 'ogg', 'opus', 'wav', 'pcm']
 
 def load_kaldi(input):
     retval = kaldiio.load_mat(input)
@@ -60,9 +60,14 @@ def load_bytes(input):
     array = np.frombuffer((middle_data.astype(dtype) - offset) / abs_max, dtype=np.float32)
     return array
 
+def load_pcm(input):
+    with open(input,"rb") as f:
+        bytes = f.read()
+    return load_bytes(bytes)
 
 DATA_TYPES = {
     "sound": lambda x: torchaudio.load(x)[0][0].numpy(),
+    "pcm": load_pcm,
     "kaldi_ark": load_kaldi,
     "bytes": load_bytes,
     "waveform": lambda x: x,
@@ -219,6 +224,9 @@ class IterableESPnetDataset(IterableDataset):
                 if audio_type not in SUPPORT_AUDIO_TYPE_SETS:
                     raise NotImplementedError(
                         f'Not supported audio type: {audio_type}')
+                if audio_type == "pcm":
+                    _type = "pcm"
+
             func = DATA_TYPES[_type]
             array = func(value)
             if self.fs is not None and name == "speech":
@@ -318,6 +326,8 @@ class IterableESPnetDataset(IterableDataset):
                         if audio_type not in SUPPORT_AUDIO_TYPE_SETS:
                             raise NotImplementedError(
                                 f'Not supported audio type: {audio_type}')
+                        if audio_type == "pcm":
+                            _type = "pcm"
                     func = DATA_TYPES[_type]
                     # Load entry
                     array = func(value)