Update app.py

app.py

@@ -15,7 +15,7 @@ else:
     p = pipeline("automatic-speech-recognition", 
                  model="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-faroese-100h")
 
-chunk_size = 30  # Adjust the chunk size as needed
+chunk_size = 10  # Adjust the chunk size as needed
 
 def transcribe(audio, state="", uploaded_audio=None):
     if uploaded_audio is not None:
@@ -25,11 +25,15 @@ def transcribe(audio, state="", uploaded_audio=None):
 
     try:
         state += "Transcribing...\n"
-        chunks = [audio[i:i + chunk_size] for i in range(0, len(audio), chunk_size)]
-        for chunk in chunks:
-            text = p(chunk)["text"]
+        if len(audio) <= chunk_size:
+            text = p(audio)["text"]
             state += text + "\n"
-            time.sleep(1)  # Simulate processing time for each chunk
+        else:
+            chunks = [audio[i:i + chunk_size] for i in range(0, len(audio), chunk_size)]
+            for chunk in chunks:
+                text = p(chunk)["text"]
+                state += text + "\n"
+                time.sleep(1)  # Simulate processing time for each chunk
         return state, state
     except Exception as e:
         return "An error occurred during transcription.", state  # Handle other exceptions
@@ -47,3 +51,4 @@ gr.Interface(
     ],
     live=True
 ).launch()
+