Update sentiment_analysis.py

sentiment_analysis.py

@@ -60,12 +60,29 @@ def analyze_sentiment(text):
         return "NEUTRAL", 0.5
 
 def transcribe_with_chunks(objections_dict):
-    """Perform real-time transcription with sentiment analysis."""
-    print("Say 'start listening' to begin transcription. Say 'stop listening' to stop.")
-    is_listening = False
-    chunks = []
-    current_chunk = []
-    chunk_start_time = time.time()
+    print("Note: If microphone access fails, please use alternative input.")
+
+    try:
+        # Try to list available microphones
+        available_mics = Microphone.list_microphone_names()
+        print(f"Available microphones: {available_mics}")
+    except Exception as e:
+        print(f"Could not detect microphones: {e}")
+
+    try:
+        # Try multiple device indices
+        mic = None
+        for device_index in range(10):  # Try first 10 device indices
+            try:
+                mic = Microphone(device_index=device_index)
+                print(f"Using microphone at device index {device_index}")
+                break
+            except Exception:
+                continue
+
+        if mic is None:
+            print("No microphone available. Please provide text input.")
+            return []
 
     # Initialize handlers with semantic search capabilities
     objection_handler = ObjectionHandler(r"C:\Users\shaik\Downloads\Sales Calls Transcriptions - Sheet3.csv")
@@ -75,7 +92,7 @@ def transcribe_with_chunks(objections_dict):
     model = SentenceTransformer('all-MiniLM-L6-v2')
 
     try:
-        with Microphone() as source:
+        with mic as source:
             recognizer.adjust_for_ambient_noise(source)
             print("Microphone calibrated. Please speak.")
             
@@ -85,6 +102,7 @@ def transcribe_with_chunks(objections_dict):
                     audio_data = recognizer.listen(source, timeout=5)
                     text = recognizer.recognize_google(audio_data)
 
+
                     if "start listening" in text.lower():
                         is_listening = True
                         print("Listening started. Speak into the microphone.")