Update app.py

app.py

@@ -1,18 +1,36 @@
 import gradio as gr
 from transformers import pipeline
 import numpy as np
+import os
 
 accuracy_classifier = pipeline(task="audio-classification", model="JohnJumon/pronunciation_accuracy")
 fluency_classifier = pipeline(task="audio-classification", model="JohnJumon/fluency_accuracy")
 prosodic_classifier = pipeline(task="audio-classification", model="JohnJumon/prosodic_accuracy")
 
 def pronunciation_scoring(audio):
-  y = audio
-  y = y.astype(np.float32)
-  y /= np.max(np.abs(y))
-  accuracy = accuracy_classifier(y)
-  fluency = fluency_classifier(y)
-  prosodic = prosodic_classifier(y)
+  accuracy_description = {
+      'Extremely Poor': 'Extremely poor pronunciation and only one or two words are recognizable',
+      'Poor': 'Poor, clumsy and rigid pronunciation of the sentence as a whole, with serious pronunciation mistakes',
+      'Average': 'The overall pronunciation of the sentence is understandable, with many pronunciation mistakes and accent, but it does not affect the understanding of basic meanings',
+      'Good': 'The overall pronunciation of the sentence is good, with a few pronunciation mistakes',
+      'Excellent': 'The overall pronunciation of the sentence is excellent, with accurate phonology and no obvious pronunciation mistakes'
+    }
+  fluency_description = {
+      'Very Influent': 'Intermittent, very influent speech, with lots of pauses, repetition, and stammering', 
+      'Influent': 'The speech is a little influent, with many pauses, repetition, and stammering', 
+      'Average': 'Fluent in general, with a few pauses, repetition, and stammering', 
+      'Fluent': 'Fluent without noticeable pauses or stammering'
+    }
+  prosodic_description = {
+      'Poor': 'Poor intonation and lots of stammering and pauses, unable to read a complete sentence', 
+      'Unstable': 'Unstable speech speed, speak too fast or too slow, without the sense of rhythm', 
+      'Stable': 'Unstable speech speed, many stammering and pauses with a poor sense of rhythm', 
+      'Almost': 'Nearly correct intonation at a stable speaking speed, nearly smooth and coherent, but with little stammering and few pauses', 
+      'Perfect': 'Correct intonation at a stable speaking speed, speak with cadence, and can speak like a native'
+    }
+  accuracy = accuracy_classifier(audio)
+  fluency = fluency_classifier(audio)
+  prosodic = prosodic_classifier(audio)
   result = {
       'accuracy': accuracy,
       'fluency': fluency,
@@ -21,13 +39,24 @@ def pronunciation_scoring(audio):
   for category, scores in result.items():
     max_score_label = max(scores, key=lambda x: x['score'])['label']
     result[category] = max_score_label
-  return result
+  return result['accuracy'], accuracy_description[result['accuracy']], result['fluency'], fluency_description[result['fluency']], result['prosodic'], prosodic_description[result['prosodic']]
 
 gradio_app = gr.Interface(
     pronunciation_scoring,
-    inputs=gr.Audio(sources=["microphone"]),
-    outputs=gr.Label(label="Result"),
+    inputs=gr.Audio(sources="microphone", type="filepath"),
+    outputs=[
+        gr.Label(label="Accuracy Result"),
+        gr.Textbox(interactive=False, show_label=False),
+        gr.Label(label="Fluency Result"),
+        gr.Textbox(interactive=False, show_label=False),
+        gr.Label(label="Prosodic Result"),
+        gr.Textbox(interactive=False, show_label=False)
+      ],
     title="Pronunciation Scoring",
+    description="This app will score your pronunciation accuracy, fluency, and prosodic (intonation)",
+    examples=[
+        [os.path.join(os.path.dirname(__file__),"audio.wav")],
+    ]
 )
 
 if __name__ == "__main__":