audiobooker

npx @mcptoolshop/audiobooker make mybook.epub --acx

Audiobooker detects dialogue, casts a distinct voice to each character, infers emotion, lets you review and correct everything before a single second is rendered, then masters the result to spec — so the output is a submittable audiobook, not just generated audio.

Install

Zero-install (Node):

npx @mcptoolshop/audiobooker --help

Python (CLI):

pipx install audiobooker-ai            # isolated CLI
uvx audiobooker --help                 # zero-install trial
pip install "audiobooker-ai[render]"   # with the TTS voice engine

Rendering audio needs the voice-soundboard TTS engine (the [render] extra) and FFmpeg on PATH (winget install ffmpeg · brew install ffmpeg · apt install ffmpeg). Everything up to render — parse, cast, compile, review — works without them. Run audiobooker diagnose to check your setup.

git clone https://github.com/mcp-tool-shop-org/audiobooker
cd audiobooker
pip install -e '.[render]'

Quick start

# One command: parse -> auto-cast -> compile -> render -> master
audiobooker make mybook.epub --acx

# ...or the staged workflow, with control at each step:
audiobooker new mybook.epub            # parse into chapters (EPUB/PDF/TXT/MD/DOCX, or a folder)
audiobooker cast --interactive         # guided per-character casting
audiobooker audition Sarah --render    # A/B candidate voices for one character
audiobooker compile                    # detect dialogue, attribute speakers, infer emotion
audiobooker report                     # what's weak? unknown-attribution rate + top lines
audiobooker review-export              # human-editable script — fix attributions
audiobooker review-import mybook_review.txt
audiobooker render --acx               # render + master to ACX spec
audiobooker master-check mybook.m4b    # PASS/FAIL vs ACX loudness/peak/noise-floor

Features

Input & structure

• EPUB, TXT, Markdown, PDF, DOCX, or a folder of per-chapter files (Scrivener/Obsidian/serialized fiction).
• TOC-driven EPUB splitting — chapter boundaries and titles from the book's own table of contents.
• DOCX splits on Word Heading 1/2/Title styles; PDF detects headings (with a scanned-PDF guard); custom --chapter-delimiter.
• Smart text cleaning, Markdown-aware stripping, footnote handling, and a reusable pronunciation lexicon (pronunciation import/export, CSV/JSON, with phoneme passthrough).

Casting & attribution

• Multi-voice synthesis with explainable, ranked voice suggestions and an audition command to A/B candidates per character.
• Interactive casting, bulk cast-fill by gender/role, named cast presets reusable across a series, and CSV cast sheets for collaborators.
• Dialogue detection + speaker attribution (optional BookNLP co-reference), alias auto-discovery, and emotion inference with adjustable intensity, scene-level mood, and genre preset packs.

Rendering & output

• M4B (chapter markers + embedded cover + series metadata), MP3, Opus, FLAC; per-chapter export; podcast/RSS feed export.
• ACX/Audible mastering (--acx) + a master-check that reports PASS/FAIL on loudness, peak, and noise floor; retail sample clips.
• Parallel rendering, a persistent render cache with resume, dynamic progress + ETA, and structured failure reports.

Workflow & ecosystem

• make one-shot pipeline · config file (.audiobookerrc / [tool.audiobooker]) · --watch mode · manifest-driven batch · shell completion.
• 7 language profiles (en/fr/de/es/ja/it/pt) · pluggable TTS engines (--engine, entry-points — bring Piper/Coqui/ElevenLabs) · scriptable --json on most commands · structured exit codes.

Publishing to ACX / Audible

Audiobooker targets the measurable ACX submission specs directly:

audiobooker render --acx               # loudnorm -20 LUFS, -3 dBTP peak, 44.1k, 192k
audiobooker master-check book.m4b      # PASS/FAIL: RMS [-23,-18], peak <= -3 dB, floor <= -60 dB
audiobooker sample --duration 180      # a mastered retail sample clip

master-check verifies the measurable requirements (loudness, peak, noise floor). ACX also has subjective/QC criteria a tool can't certify — but you'll never get bounced for a loudness violation again.

CLI commands

Command	Description
make <file>	One-shot: new → compile → auto-cast → render
new <file|folder>	Create a project from EPUB/TXT/MD/PDF/DOCX or a folder
from-stdin	Create a project from piped text
cast <char> <voice> · cast --interactive	Assign voices (or guided per-speaker casting)
cast-suggest · cast-apply --auto · cast-fill	Suggest / auto-apply / bulk-assign voices
cast-preset save|list|apply|delete	Reusable cast presets across books
audition <char>	A/B ranked candidate voices for one character (--render)
compile	Detect dialogue, attribute speakers, infer emotion
report	Compile quality: unknown rate, top unattributed lines, emotion mix
review-export · review-import <file>	Human-editable review round-trip
render	Render the audiobook (--acx, --format, --split, --bitrate, --engine, --watch, --cover, -j N)
sample · master-check <file>	Mastered retail sample · ACX compliance check
export-chapters · podcast	Chapter cue sheet (ffmetadata/cue/json) · podcast RSS feed
preview · batch · diagnose	Voice QA clip · batch/--manifest · environment check
voices · chapters · speakers · info · status · cache · emotions · pronunciation · completion	Inspect & manage

Every command supports -h/--help. Global flags: --silent, --debug. Exit codes: 0 ok · 1 user error · 2 runtime · 3 partial (batch).

Configuration

Set defaults once instead of re-passing flags — .audiobookerrc (TOML) next to your book, or [tool.audiobooker] in pyproject.toml. Precedence is CLI flag > project config > user config (~/.audiobookerrc) > built-in defaults.

# .audiobookerrc
output_format = "m4b"
output_profile = "acx"
lang = "en"
jobs = 4
booknlp_mode = "auto"

Pluggable TTS engines

The default engine is voice-soundboard, but the synthesis backend is swappable via setuptools entry-points (audiobooker.tts_engines):

audiobooker render --engine piper      # or set AUDIOBOOKER_ENGINE=piper

A plugin (pip install audiobooker-piper) registers itself; no fork required.

Python API

from audiobooker import AudiobookProject

project = AudiobookProject.from_epub("mybook.epub")   # or from_docx / from_pdf / from_folder / from_string
project.cast("narrator", "bm_george", emotion="calm")
project.cast("Alice", "af_bella", emotion="warm")
project.compile()                                     # dialogue, speakers, emotion
project.render("mybook.m4b")                          # resumes from cache on re-run
project.save("mybook.audiobooker")

render(...) and compile(...) accept an injected engine= (any object implementing the TTSEngine protocol) and a progress callback — embed audiobooker in a GUI or service.

Architecture

audiobooker/
├── parser/      # EPUB, PDF, TXT/MD, DOCX, folder, language-aware splitting
├── language/    # 7 language profiles (quotes, speaker verbs, chapter patterns)
├── casting/     # dialogue detection, voice suggestion, presets, cast-fill
├── nlp/         # BookNLP adapter, emotion inference, speaker/alias resolution
├── renderer/    # synthesis, chapter+utterance cache, mastering, assembly, RSS
├── config_file.py · review.py · project.py · cli.py

Source (EPUB/PDF/DOCX/TXT/folder) -> Parser -> Chapters -> Dialogue & Emotion ->
Casting -> Review/Edit -> TTS (pluggable) -> cached audio -> FFmpeg master -> M4B/MP3/Opus/FLAC

Security & data scope

• Network: none — no telemetry, no data storage, no credentials. Reads your book files, writes audio + cache to your output dirs.
• Permissions: read access to inputs, write access to outputs; optional FFmpeg + a TTS engine on PATH.
• See SECURITY.md.

Scorecard

Gate	Status
A. Security Baseline	PASS
B. Error Handling	PASS
C. Operator Docs	PASS
D. Shipping Hygiene	PASS
E. Identity	PASS

License

MIT

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Built by MCP Tool Shop