177 lines
8.0 KiB
Python
177 lines
8.0 KiB
Python
"""
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audiobook_nem.py
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────────────────
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Generate the Book of the Nem audiobook — one unique voice per book/section.
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Usage:
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python audiobook_nem.py
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To skip a section, comment out its entry in BOOKS below.
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Output .wav files are written to OUTPUT_DIR (created automatically).
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"""
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import re
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import numpy as np
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import soundfile as sf
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import torch
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from pathlib import Path
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from kokoro import KPipeline
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# ── Config ─────────────────────────────────────────────────────────────────────
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_FIXED_FILE = Path("Audio Master Nem Full (TTS Fixed).txt")
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_ORIG_FILE = Path("Audio Master Nem Full.txt")
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SOURCE_FILE = _FIXED_FILE if _FIXED_FILE.exists() else _ORIG_FILE
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OUTPUT_DIR = Path("output_audiobook")
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SAMPLE_RATE = 24000
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SPEED = 1.0
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LANG_CODE = "a" # 'a' = American English
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# ── Available Kokoro voices (American English, lang_code='a') ──────────────────
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# af_heart – warm American female [downloaded]
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# af_nicole – American female [downloaded]
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# am_adam – American male (deep) [downloaded]
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# am_echo – American male [downloaded]
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# am_eric – American male [downloaded]
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# am_fenrir – American male [downloaded]
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# am_liam – American male [downloaded]
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# am_michael – American male (clear) [downloaded]
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# am_onyx – American male [downloaded]
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# am_puck – American male [downloaded]
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# am_santa – American male [downloaded] (not used)
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# ── Book definitions ───────────────────────────────────────────────────────────
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# Format: (label, start_marker, voice, output_wav)
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# start_marker – exact text of the FIRST line of the section header in the source
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# (leading/trailing whitespace is ignored when matching)
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# voice – Kokoro voice name
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# output_wav – filename saved inside OUTPUT_DIR
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#
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# Comment out any line to skip that section entirely.
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BOOKS = [
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# label start_marker voice output_wav
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("Introduction", "Introduction", "af_heart", "00_introduction.wav"),
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("Book of Hagoth", "THE BOOK OF HAGOTH", "am_fenrir", "01_hagoth.wav"),
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("Shi-Tugo I", "THE FIRST BOOK OF SHI-TUGO", "am_eric", "02_shi_tugo_1.wav"),
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("Sanempet", "THE BOOK OF SANEMPET", "am_liam", "03_sanempet.wav"),
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("Oug", "THE BOOK OF OUG", "am_michael", "04_oug.wav"),
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("Temple Writings of Oug", "THE BOOK OF", "am_michael", "05_temple_writings_oug.wav"),
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("Sacred Temple Writings", "THE SACRED", "am_michael", "06_sacred_temple_writings.wav"),
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("Samuel the Lamanite I", "THE FIRST BOOK", "am_echo", "07_samuel_lamanite_1.wav"),
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("Samuel the Lamanite II", "THE SECOND BOOK", "am_echo", "08_samuel_lamanite_2.wav"),
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("Manti", "THE BOOK OF MANTI", "am_onyx", "09_manti.wav"),
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("Pa Nat I", "THE FIRST BOOK OF PA NAT", "af_nicole", "10_pa_nat_1.wav"),
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("Moroni I", "THE FIRST BOOK OF MORONI", "am_adam", "11_moroni_1.wav"),
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("Moroni II", "THE SECOND BOOK OF MORONI", "am_adam", "12_moroni_2.wav"),
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("Moroni III", "THE THIRD BOOK OF MORONI", "am_adam", "13_moroni_3.wav"),
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("Shioni", "THE BOOK OF SHIONI", "am_puck", "14_shioni.wav"),
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]
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# ── Helpers ────────────────────────────────────────────────────────────────────
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def load_and_split(source: Path, books: list) -> dict[str, str]:
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"""
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Read the source file and split it into sections keyed by label.
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Each section starts at its start_marker line and ends just before the
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next section's start_marker.
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"""
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raw_lines = source.read_text(encoding="utf-8").splitlines()
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# Build a mapping: marker_text → index in BOOKS
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markers = [(label, marker.strip()) for label, marker, _, _ in books]
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# Find the line index of each marker's first occurrence
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marker_positions: list[tuple[int, int]] = [] # (line_idx, books_idx)
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for book_idx, (label, marker) in enumerate(markers):
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for line_idx, line in enumerate(raw_lines):
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if line.strip() == marker:
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marker_positions.append((line_idx, book_idx))
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break
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else:
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print(f" ⚠ Marker not found for '{label}': '{marker}' — skipping")
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marker_positions.sort(key=lambda x: x[0])
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sections: dict[str, str] = {}
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for rank, (line_idx, book_idx) in enumerate(marker_positions):
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label = markers[book_idx][0]
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if rank + 1 < len(marker_positions):
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end_line = marker_positions[rank + 1][0]
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else:
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end_line = len(raw_lines)
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text = "\n".join(raw_lines[line_idx:end_line]).strip()
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sections[label] = text
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return sections
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def clean_text(text: str) -> str:
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"""
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Strip formatting artifacts, underscores, and normalise whitespace
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so the TTS receives clean prose.
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"""
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# Remove lines that are pure underscores (horizontal rules)
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text = re.sub(r"^_{3,}\s*$", "", text, flags=re.MULTILINE)
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# Remove leading chapter headers that are all-caps lines
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# (keep them as natural spoken title for context)
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# Collapse excess blank lines
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text = re.sub(r"\n{3,}", "\n\n", text)
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return text.strip()
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def generate_audio(pipeline: KPipeline, text: str, voice: str,
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output_path: Path) -> None:
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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(str(output_path), audio, SAMPLE_RATE)
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duration = len(audio) / SAMPLE_RATE
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print(f" ✓ Saved '{output_path.name}' ({duration:.1f}s)")
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else:
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print(f" ✗ No audio produced for voice='{voice}'")
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# ── Main ───────────────────────────────────────────────────────────────────────
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def main() -> None:
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device = "cuda" if torch.cuda.is_available() else "cpu"
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print(f"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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OUTPUT_DIR.mkdir(exist_ok=True)
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print(f"\nSource: '{SOURCE_FILE}'"
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+ (" ✓ (TTS fixed)" if SOURCE_FILE == _FIXED_FILE else
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" ⚠ (original — run 'Apply Fixes to Text' in the GUI to use phonetic fixes)"))
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sections = load_and_split(SOURCE_FILE, BOOKS)
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print(f" Found {len(sections)} sections.\n")
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print("Initialising Kokoro pipeline …")
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pipeline = KPipeline(lang_code=LANG_CODE)
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for label, marker, voice, wav_name in BOOKS:
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if label not in sections:
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continue # marker was not found; warning already printed
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print(f"\n[{label}] voice={voice} → {wav_name}")
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text = clean_text(sections[label])
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if not text:
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print(" ⚠ Empty text — skipping")
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continue
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out_path = OUTPUT_DIR / wav_name
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generate_audio(pipeline, text, voice, out_path)
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print("\nDone.")
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if __name__ == "__main__":
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main()
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