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import gradio as gr
import librosa
import numpy as np
import matplotlib.pyplot as plt
import tempfile
def extract_audio_features(audio_file):
y, sr = librosa.load(audio_file, sr=None)
mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13)
pitches, magnitudes = librosa.piptrack(y=y, sr=sr)
pitches = pitches[(magnitudes > np.median(magnitudes)) & (pitches > 0)]
energy = librosa.feature.rms(y=y)[0]
return mfccs, pitches, energy
def analyze_voice_stress(audio_file):
if not audio_file:
return "No audio file provided.", None
try:
mfccs, pitches, energy = extract_audio_features(audio_file)
stress_level = (np.var(mfccs) + (np.var(pitches) if len(pitches) > 0 else 0) + np.var(energy)) / 3
normalized_stress = min(100, (stress_level / 1000) * 100)
fig, axs = plt.subplots(3, 1, figsize=(10, 12))
plots = [
(mfccs, 'MFCCs', 'MFCC Coefficient', 'imshow', {'aspect': 'auto', 'origin': 'lower'}),
(pitches, 'Pitch', 'Frequency (Hz)', 'plot', {}),
(energy, 'Energy', 'RMS Energy', 'plot', {})
]
for i, (data, title, ylabel, plot_type, plot_args) in enumerate(plots):
getattr(axs[i], plot_type)(data, **plot_args)
axs[i].set_title(title)
axs[i].set_ylabel(ylabel)
axs[2].set_xlabel('Time')
plt.tight_layout()
with tempfile.NamedTemporaryFile(delete=False, suffix='.png') as temp_file:
plt.savefig(temp_file.name)
plt.close()
stress_interpretation = "Low" if normalized_stress < 33 else "Medium" if normalized_stress < 66 else "High"
return f"{normalized_stress:.2f}% - {stress_interpretation} Stress", temp_file.name
except Exception as e:
return str(e), None
def create_voice_stress_tab():
with gr.Row():
with gr.Column(scale=2):
input_audio = gr.Audio(label="Input Audio", type="filepath")
with gr.Row():
clear_btn = gr.Button("Clear", scale=1)
submit_btn = gr.Button("Analyze", scale=1, elem_classes="submit")
with gr.Column(scale=1):
output_stress = gr.Label(label="Stress Level")
output_plot = gr.Image(label="Stress Analysis Plot")
submit_btn.click(analyze_voice_stress, inputs=[input_audio], outputs=[output_stress, output_plot])
clear_btn.click(lambda: (None, None, None), outputs=[input_audio, output_stress, output_plot])
gr.Examples(["./assets/audio/fitness.wav"], inputs=[input_audio])
with gr.Blocks() as demo:
gr.Markdown("# Voice Stress Analysis")
create_voice_stress_tab() |