Initial commit: audiobook generator, proper noun auditor GUI

render_voices.py

@@ -0,0 +1,44 @@
+import torch
+import numpy as np
+import soundfile as sf
+from kokoro import KPipeline
+from text_input import TEXT
+
+# ── Device setup ──────────────────────────────────────────────────────────────
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"Using device: {device}")
+if device == "cuda":
+    print(f"GPU: {torch.cuda.get_device_name(0)}")
+
+SAMPLE_RATE = 24000
+SPEED = 1.0
+VOICES = [
+    ("af_heart",   "output_af_heart.wav"),    # warm American female
+    ("am_michael", "output_am_michael.wav"),   # best American male
+]
+
+pipeline = KPipeline(lang_code="a")
+
+
+def generate(voice: str, output_file: str) -> None:
+    print(f"\nGenerating '{voice}' → {output_file} …")
+    chunks = []
+    for _, _, chunk_audio in pipeline(TEXT, voice=voice, speed=SPEED):
+        if hasattr(chunk_audio, "numpy"):
+            chunk_audio = chunk_audio.cpu().numpy()
+        chunk_audio = np.atleast_1d(chunk_audio.squeeze())
+        if chunk_audio.size > 0:
+            chunks.append(chunk_audio)
+
+    if chunks:
+        audio = np.concatenate(chunks, axis=0)
+        sf.write(output_file, audio, SAMPLE_RATE)
+        print(f"  ✓ Saved '{output_file}'  ({len(audio) / SAMPLE_RATE:.1f}s, {SAMPLE_RATE} Hz)")
+    else:
+        print(f"  ✗ No audio produced for '{voice}'")
+
+
+for voice, path in VOICES:
+    generate(voice, path)
+
+print("\nDone.")