diff --git a/data/test/audios/1ch_nihaomiya.wav b/data/test/audios/1ch_nihaomiya.wav
new file mode 100644
index 00000000..4618d412
--- /dev/null
+++ b/data/test/audios/1ch_nihaomiya.wav
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f7f5a0a4efca1e83463cb44460c66b56fb7cd673eb6da37924637bc05ef758d
+size 1440044
diff --git a/modelscope/pipelines/audio/kws_farfield_pipeline.py b/modelscope/pipelines/audio/kws_farfield_pipeline.py
index 62f58fee..e2f618fa 100644
--- a/modelscope/pipelines/audio/kws_farfield_pipeline.py
+++ b/modelscope/pipelines/audio/kws_farfield_pipeline.py
@@ -4,6 +4,9 @@ import io
 import wave
 from typing import Any, Dict
 
+import numpy
+import soundfile as sf
+
 from modelscope.fileio import File
 from modelscope.metainfo import Pipelines
 from modelscope.outputs import OutputKeys
@@ -37,7 +40,6 @@ class KWSFarfieldPipeline(Pipeline):
         self.model.eval()
         frame_size = self.INPUT_CHANNELS * self.SAMPLE_WIDTH
         self._nframe = self.model.size_in // frame_size
-        self.frame_count = 0
 
     def preprocess(self, inputs: Input, **preprocess_params) -> Dict[str, Any]:
         if isinstance(inputs, bytes):
@@ -54,35 +56,36 @@ class KWSFarfieldPipeline(Pipeline):
         input_file = inputs['input_file']
         if isinstance(input_file, str):
             input_file = File.read(input_file)
-        if isinstance(input_file, bytes):
-            input_file = io.BytesIO(input_file)
-        self.frame_count = 0
+        frames, samplerate = sf.read(io.BytesIO(input_file), dtype='int16')
+        if len(frames.shape) == 1:
+            frames = numpy.stack((frames, frames, numpy.zeros_like(frames)), 1)
+
         kws_list = []
-        with wave.open(input_file, 'rb') as fin:
-            if 'output_file' in inputs:
-                with wave.open(inputs['output_file'], 'wb') as fout:
-                    fout.setframerate(self.SAMPLE_RATE)
-                    fout.setnchannels(self.OUTPUT_CHANNELS)
-                    fout.setsampwidth(self.SAMPLE_WIDTH)
-                    self._process(fin, kws_list, fout)
-            else:
-                self._process(fin, kws_list)
+        if 'output_file' in inputs:
+            with wave.open(inputs['output_file'], 'wb') as fout:
+                fout.setframerate(self.SAMPLE_RATE)
+                fout.setnchannels(self.OUTPUT_CHANNELS)
+                fout.setsampwidth(self.SAMPLE_WIDTH)
+                self._process(frames, kws_list, fout)
+        else:
+            self._process(frames, kws_list)
         return {OutputKeys.KWS_LIST: kws_list}
 
     def _process(self,
-                 fin: wave.Wave_read,
+                 frames: numpy.ndarray,
                  kws_list,
                  fout: wave.Wave_write = None):
-        data = fin.readframes(self._nframe)
-        while len(data) >= self.model.size_in:
-            self.frame_count += self._nframe
+        for start_index in range(0, frames.shape[0], self._nframe):
+            end_index = start_index + self._nframe
+            if end_index > frames.shape[0]:
+                end_index = frames.shape[0]
+            data = frames[start_index:end_index, :].tobytes()
             result = self.model.forward_decode(data)
             if fout:
                 fout.writeframes(result['pcm'])
             if 'kws' in result:
-                result['kws']['offset'] += self.frame_count / self.SAMPLE_RATE
+                result['kws']['offset'] += start_index / self.SAMPLE_RATE
                 kws_list.append(result['kws'])
-            data = fin.readframes(self._nframe)
 
     def postprocess(self, inputs: Dict[str, Any], **kwargs) -> Dict[str, Any]:
         return inputs
diff --git a/tests/pipelines/test_key_word_spotting_farfield.py b/tests/pipelines/test_key_word_spotting_farfield.py
index fea7afd7..f8c167de 100644
--- a/tests/pipelines/test_key_word_spotting_farfield.py
+++ b/tests/pipelines/test_key_word_spotting_farfield.py
@@ -8,6 +8,7 @@ from modelscope.utils.constant import Tasks
 from modelscope.utils.test_utils import test_level
 
 TEST_SPEECH_FILE = 'data/test/audios/3ch_nihaomiya.wav'
+TEST_SPEECH_FILE_MONO = 'data/test/audios/1ch_nihaomiya.wav'
 TEST_SPEECH_URL = 'https://modelscope.cn/api/v1/models/damo/' \
                   'speech_dfsmn_kws_char_farfield_16k_nihaomiya/repo' \
                   '?Revision=master&FilePath=examples/3ch_nihaomiya.wav'
@@ -26,6 +27,16 @@ class KWSFarfieldTest(unittest.TestCase):
         self.assertEqual(len(result['kws_list']), 5)
         print(result['kws_list'][-1])
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    def test_mono(self):
+        kws = pipeline(Tasks.keyword_spotting, model=self.model_id)
+        inputs = {
+            'input_file': os.path.join(os.getcwd(), TEST_SPEECH_FILE_MONO)
+        }
+        result = kws(inputs)
+        self.assertEqual(len(result['kws_list']), 5)
+        print(result['kws_list'][-1])
+
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_url(self):
         kws = pipeline(Tasks.keyword_spotting, model=self.model_id)