Update app.py

app.py

@@ -11,25 +11,42 @@ pipe = pipeline(
 translator = pipeline("text2text-generation", model="Baghdad99/saad-hausa-text-to-english-text")
 tts = pipeline("text-to-speech", model="Baghdad99/english_voice_tts")
 
-# Define the function to translate speech
 def translate_speech(audio):
     # Separate the sample rate and the audio data
     sample_rate, audio_data = audio
 
     # Use the speech recognition pipeline to transcribe the audio
-    transcription = pipe(audio_data)["transcription"]
+    output = pipe(audio_data)
+    print(f"Output: {output}")  # Print the output to see what it contains
 
-    # Use the translation pipeline to translate the transcription
-    translated_text = translator(transcription, return_tensors="pt", padding=True)
+    # Check if the output contains 'transcription'
+    if 'transcription' in output:
+        transcription = output["transcription"]
+    else:
+        print("The output does not contain 'transcription'")
+        return
 
-    # Use the text-to-speech pipeline to synthesize the translated text
-    synthesised_speech = tts(translated_text, return_tensors='pt')
+    # Rest of your code...
 
-    # Define the max_range variable
-    max_range = 32767  # You can adjust this value based on your requirements
-    synthesised_speech = (synthesised_speech.numpy() * max_range).astype(np.int16)
+# # Define the function to translate speech
+# def translate_speech(audio):
+#     # Separate the sample rate and the audio data
+#     sample_rate, audio_data = audio
 
-    return 16000, synthesised_speech
+#     # Use the speech recognition pipeline to transcribe the audio
+#     transcription = pipe(audio_data)["transcription"]
+
+#     # Use the translation pipeline to translate the transcription
+#     translated_text = translator(transcription, return_tensors="pt", padding=True)
+
+#     # Use the text-to-speech pipeline to synthesize the translated text
+#     synthesised_speech = tts(translated_text, return_tensors='pt')
+
+#     # Define the max_range variable
+#     max_range = 32767  # You can adjust this value based on your requirements
+#     synthesised_speech = (synthesised_speech.numpy() * max_range).astype(np.int16)
+
+#     return 16000, synthesised_speech
 
 
 # Define the Gradio interface