Update app.py

app.py

@@ -3,18 +3,21 @@ subprocess.run(["pip", "install", "gradio", "--upgrade"])
 subprocess.run(["pip", "install", "transformers"])
 subprocess.run(["pip", "install", "torchaudio", "--upgrade"])
 
+import numpy as np
 import gradio as gr
 from transformers import WhisperProcessor, WhisperForConditionalGeneration
 
 # Load Whisper ASR model and processor
 model_name = "openai/whisper-small"
-processor = WhisperProcessor.from_pretrained(model_name)
+processor = WhisperProcessor.from_pretrained(model_name, sampling_rate=44100)
 model = WhisperForConditionalGeneration.from_pretrained(model_name)
 forced_decoder_ids = processor.get_decoder_prompt_ids(language="italian", task="transcribe")
 
+
+
 def transcribe_audio(input_audio):
-    # Process audio using the Whisper processor
-    input_features = processor(input_audio, return_tensors="pt").input_features
+    input_audio_np = np.array(input_audio[0].data)
+    input_features = processor(input_audio_np, return_tensors="pt").input_features
 
     # Generate token ids
     predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids)
@@ -26,7 +29,7 @@ def transcribe_audio(input_audio):
 
 iface = gr.Interface(
     fn=transcribe_audio,
-    inputs=gr.Audio(type="numpy", label="Speak"),
+    inputs=gr.Audio(sources=["microphone"], label="Speak"),
     outputs="text",
     live=True
 )