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Runtime error
| import streamlit as st | |
| from transformers import pipeline | |
| # Load the model pipeline | |
| model = pipeline("audio-classification", model="HareemFatima/distilhubert-finetuned-stutterdetection") | |
| # Streamlit app | |
| def main(): | |
| st.title("Stutter Classification App") | |
| audio_input = st.audio("Capture Audio", format="audio/wav", start_recording=True, channels=1) | |
| if st.button("Stop Recording"): | |
| # Assuming the recording is saved as "recording.wav" | |
| recording_path = "recording.wav" | |
| # Call the model pipeline to classify the audio | |
| prediction = model(recording_path) | |
| # Get the predicted label | |
| predicted_label = prediction[0]["label"] | |
| # Map the label to the corresponding stutter type | |
| if predicted_label == 0: | |
| stutter_type = "nonstutter" | |
| elif predicted_label == 1: | |
| stutter_type = "prolongation" | |
| elif predicted_label == 2: | |
| stutter_type = "repetition" | |
| elif predicted_label == 3: | |
| stutter_type = "blocks" | |
| else: | |
| stutter_type = "Unknown" | |
| st.write("Predicted Stutter Type:", stutter_type) | |
| if __name__ == "__main__": | |
| main() | |