diff --git a/paddlespeech/server/utils/audio_handler.py b/paddlespeech/server/utils/audio_handler.py
new file mode 100644
index 0000000000000000000000000000000000000000..3a864a781354f4a525c3150d48ec6059242922e7
--- /dev/null
+++ b/paddlespeech/server/utils/audio_handler.py
@@ -0,0 +1,86 @@
+import numpy as np
+import logging
+import argparse
+import asyncio
+import codecs
+import json
+import logging
+import os
+
+import numpy as np
+import soundfile
+import websockets
+from paddlespeech.cli.log import logger
+class ASRAudioHandler:
+    def __init__(self, url="127.0.0.1", port=8090):
+        self.url = url
+        self.port = port
+        self.url = "ws://" + self.url + ":" + str(self.port) + "/ws/asr"
+
+    def read_wave(self, wavfile_path: str):
+        samples, sample_rate = soundfile.read(wavfile_path, dtype='int16')
+        x_len = len(samples)
+
+        chunk_size = 85 * 16  #80ms, sample_rate = 16kHz
+        if x_len % chunk_size!= 0:
+            padding_len_x = chunk_size - x_len % chunk_size
+        else:
+            padding_len_x = 0
+
+        padding = np.zeros((padding_len_x), dtype=samples.dtype)
+        padded_x = np.concatenate([samples, padding], axis=0)
+
+        assert (x_len + padding_len_x) % chunk_size == 0
+        num_chunk = (x_len + padding_len_x) / chunk_size
+        num_chunk = int(num_chunk)
+        for i in range(0, num_chunk):
+            start = i * chunk_size
+            end = start + chunk_size
+            x_chunk = padded_x[start:end]
+            yield x_chunk
+
+    async def run(self, wavfile_path: str):
+        logging.info("send a message to the server")
+        # self.read_wave()
+        # send websocket handshake protocal
+        async with websockets.connect(self.url) as ws:
+            # server has already received handshake protocal
+            # client start to send the command
+            audio_info = json.dumps(
+                {
+                    "name": "test.wav",
+                    "signal": "start",
+                    "nbest": 5
+                },
+                sort_keys=True,
+                indent=4,
+                separators=(',', ': '))
+            await ws.send(audio_info)
+            msg = await ws.recv()
+            logger.info("receive msg={}".format(msg))
+
+            # send chunk audio data to engine
+            for chunk_data in self.read_wave(wavfile_path):
+                await ws.send(chunk_data.tobytes())
+                msg = await ws.recv()
+                msg = json.loads(msg)
+                logger.info("receive msg={}".format(msg))
+
+            # finished 
+            audio_info = json.dumps(
+                {
+                    "name": "test.wav",
+                    "signal": "end",
+                    "nbest": 5
+                },
+                sort_keys=True,
+                indent=4,
+                separators=(',', ': '))
+            await ws.send(audio_info)
+            msg = await ws.recv()
+            
+            # decode the bytes to str
+            msg = json.loads(msg)
+            logger.info("final receive msg={}".format(msg))
+            result = msg
+            return result
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