diff --git a/data_utils/audio.py b/data_utils/audio.py
index 29fdd0bd..3891f5b9 100644
--- a/data_utils/audio.py
+++ b/data_utils/audio.py
@@ -64,8 +64,6 @@ class AudioSegment(object):
         :rtype: AudioSegment
         """
         samples, sample_rate = soundfile.read(file, dtype='float32')
-        print(samples)
-        print(sample_rate)
         return cls(samples, sample_rate)
 
     @classmethod
diff --git a/demo_server.py b/demo_server.py
index 4a3feb13..85f69483 100644
--- a/demo_server.py
+++ b/demo_server.py
@@ -1,5 +1,6 @@
 import os
 import time
+import random
 import argparse
 import distutils.util
 from time import gmtime, strftime
@@ -8,9 +9,10 @@ import struct
 import wave
 import pyaudio
 import paddle.v2 as paddle
+from utils import print_arguments
 from data_utils.data import DataGenerator
 from model import DeepSpeech2Model
-import utils
+from data_utils.utils import read_manifest
 
 parser = argparse.ArgumentParser(description=__doc__)
 parser.add_argument(
@@ -38,6 +40,11 @@ parser.add_argument(
     default='mean_std.npz',
     type=str,
     help="Manifest path for normalizer. (default: %(default)s)")
+parser.add_argument(
+    "--warmup_manifest_path",
+    default='datasets/manifest.test',
+    type=str,
+    help="Manifest path for warmup test. (default: %(default)s)")
 parser.add_argument(
     "--specgram_type",
     default='linear',
@@ -77,7 +84,7 @@ parser.add_argument(
     "(default: %(default)s)")
 parser.add_argument(
     "--beam_size",
-    default=500,
+    default=100,
     type=int,
     help="Width for beam search decoding. (default: %(default)d)")
 parser.add_argument(
@@ -134,7 +141,6 @@ class AsrRequestHandler(SocketServer.BaseRequestHandler):
 
         print("Received utterance[length=%d] from %s, saved to %s." %
               (len(data), self.client_address[0], filename))
-        #filename = "/home/work/.cache/paddle/dataset/speech/Libri/train-other-500/LibriSpeech/train-other-500/811/130143/811-130143-0025.flac"
         start_time = time.time()
         transcript = self.server.audio_process_handler(filename)
         finish_time = time.time()
@@ -149,7 +155,7 @@ class AsrRequestHandler(SocketServer.BaseRequestHandler):
         timestamp = strftime("%Y%m%d%H%M%S", gmtime())
         out_filename = os.path.join(
             self.server.speech_save_dir,
-            timestamp + "_" + self.client_address[0] + "_" + ".wav")
+            timestamp + "_" + self.client_address[0] + ".wav")
         # write to wav file
         file = wave.open(out_filename, 'wb')
         file.setnchannels(1)
@@ -160,6 +166,22 @@ class AsrRequestHandler(SocketServer.BaseRequestHandler):
         return out_filename
 
 
+def warm_up_test(audio_process_handler,
+                 manifest_path,
+                 num_test_cases,
+                 random_seed=0):
+    manifest = read_manifest(manifest_path)
+    rng = random.Random(random_seed)
+    samples = rng.sample(manifest, num_test_cases)
+    for idx, sample in enumerate(samples):
+        print("Warm-up Test Case %d: %s", idx, sample['audio_filepath'])
+        start_time = time.time()
+        transcript = audio_process_handler(sample['audio_filepath'])
+        finish_time = time.time()
+        print("Response Time: %f, Transcript: %s" %
+              (finish_time - start_time, transcript))
+
+
 def start_server():
     data_generator = DataGenerator(
         vocab_filepath=args.vocab_filepath,
@@ -188,6 +210,14 @@ def start_server():
             num_processes=1)
         return result_transcript[0]
 
+    print('-----------------------------------------------------------')
+    print('Warming up ...')
+    warm_up_test(
+        audio_process_handler=file_to_transcript,
+        manifest_path=args.warmup_manifest_path,
+        num_test_cases=3)
+    print('-----------------------------------------------------------')
+
     server = AsrTCPServer(
         server_address=(args.host_ip, args.host_port),
         RequestHandlerClass=AsrRequestHandler,
@@ -199,7 +229,7 @@ def start_server():
 
 
 def main():
-    utils.print_arguments(args)
+    print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=1)
     start_server()