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import random |
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import time |
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import numpy as np |
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def clone_voice(samples, traits): |
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time.sleep(3) |
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duration = 5 |
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sample_rate = 44100 |
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t = np.linspace(0, duration, int(sample_rate * duration), False) |
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waveform = np.sin(440 * 2 * np.pi * t) * 0.5 |
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return (waveform * 32767).astype(np.int16) |
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def restore_speech(samples): |
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time.sleep(3) |
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duration = 5 |
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sample_rate = 44100 |
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t = np.linspace(0, duration, int(sample_rate * duration), False) |
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waveform = np.sin(440 * 2 * np.pi * t) * 0.5 |
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return (waveform * 32767).astype(np.int16) |
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def generate_historical_dialogue(personality, user_input): |
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time.sleep(2) |
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responses = [ |
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f"As {personality}, I find your question about '{user_input}' intriguing. In my time, we...", |
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f"Interesting inquiry about '{user_input}'. During my era as {personality}, I observed that...", |
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f"Your question on '{user_input}' touches upon a crucial aspect of my work as {personality}. Let me explain...", |
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f"Ah, '{user_input}'! This reminds me of a time when I, {personality}, encountered a similar situation...", |
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f"From the perspective of {personality}, I can say that '{user_input}' relates to my experiences in the following way..." |
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] |
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response = random.choice(responses) |
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st.session_state.conversation_history.append(f"You: {user_input}") |
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st.session_state.conversation_history.append(f"{personality}: {response}") |
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return response |
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