Update app.py

app.py

@@ -9,7 +9,7 @@ BATCH_SIZE = 1
 
 device = 0 if torch.cuda.is_available() else "cpu"
 
-def score(test_file, ref_file, score_list_nis, score_list_is, return_timestamps):
+def score_file(test_file, ref_file, score_list_nis, score_list_is):
     score_list = []
     if score_list_nis is not None:
         score_list += score_list_nis
@@ -19,16 +19,23 @@ def score(test_file, ref_file, score_list_nis, score_list_is, return_timestamps)
     scores = mySpeechScore(test_path=test_file, reference_path=ref_file, window=None, score_rate=16000, return_mean=False)
     return scores
 
+def score_mic(test_file, score_list_nis):
+    score_list = []
+    if score_list_nis is not None:
+        score_list += score_list_nis       
+    mySpeechScore = SpeechScore(score_list)  
+    scores = mySpeechScore(test_path=test_file, reference_path=ref_file, window=None, score_rate=16000, return_mean=False)
+    return scores
 
 demo = gr.Blocks()
 
 file_score = gr.Interface(
-    fn=score,
+    fn=score_file,
     inputs=[
         gr.Audio(sources=["upload"], label="test file", type="filepath"),
         gr.Audio(sources=["upload"], label="reference file", type="filepath"),
         gr.Dropdown(
-            ["DNSMOS", "SRMR"], value=["DNSMOS", "SRMR"], multiselect=True, label="Non-Intrusive Scores", info="Choose scores to include, no reference audio is required."
+            ["DNSMOS", "SRMR"], value=["DNSMOS"], multiselect=True, label="Non-Intrusive Scores", info="Choose scores to include, no reference audio is required."
         ),
         gr.Dropdown(
             ["PESQ", 'NB_PESQ', 'STOI', 'SISDR',
@@ -47,7 +54,7 @@ file_score = gr.Interface(
 )
 
 mic_score = gr.Interface(
-    fn=score,
+    fn=score_mic,
     inputs=[
         gr.Audio(sources=["microphone"],
                 waveform_options=gr.WaveformOptions(