45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
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import torch
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import numpy as np
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import soundfile as sf
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from kokoro import KPipeline
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from text_input import TEXT
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# ── Device setup ──────────────────────────────────────────────────────────────
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device = "cuda" if torch.cuda.is_available() else "cpu"
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print(f"Using device: {device}")
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if device == "cuda":
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print(f"GPU: {torch.cuda.get_device_name(0)}")
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SAMPLE_RATE = 24000
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SPEED = 1.0
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VOICES = [
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("af_heart", "output_af_heart.wav"), # warm American female
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("am_michael", "output_am_michael.wav"), # best American male
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]
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pipeline = KPipeline(lang_code="a")
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def generate(voice: str, output_file: str) -> None:
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print(f"\nGenerating '{voice}' → {output_file} …")
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chunks = []
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for _, _, chunk_audio in pipeline(TEXT, voice=voice, speed=SPEED):
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if hasattr(chunk_audio, "numpy"):
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chunk_audio = chunk_audio.cpu().numpy()
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chunk_audio = np.atleast_1d(chunk_audio.squeeze())
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if chunk_audio.size > 0:
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chunks.append(chunk_audio)
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if chunks:
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audio = np.concatenate(chunks, axis=0)
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sf.write(output_file, audio, SAMPLE_RATE)
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print(f" ✓ Saved '{output_file}' ({len(audio) / SAMPLE_RATE:.1f}s, {SAMPLE_RATE} Hz)")
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else:
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print(f" ✗ No audio produced for '{voice}'")
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for voice, path in VOICES:
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generate(voice, path)
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print("\nDone.")
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