Audiobook Production

Audiobook production

An audiobook is not a long TTS clip. It is a **structured deliverable of many

chapterized files**, each of which must pass an automated loudness/noise gate,

carry the right metadata, and sound like the same performer that opened Chapter

• The problems that dominate this work — voice drift over ten hours, a proper

noun mispronounced 40 times, a footnote that makes no sense read aloud, a file

rejected for a -58 dB noise floor, a platform that silently bans AI narration —

do not exist in short-clip synthesis. This skill is about managing hour-scale

production, not about generating one good sentence.

This is a craft skill, provider-neutral. Generative voice tools are

referenced by capability (pronunciation lexicon, SSML support, seed/consistency

control, per-chapter regeneration), not by brand. Specific tools and retail

platforms are named only as illustrative examples or as dated policy facts.

Labels used below:

• [Fact] — documented in a primary/official source, cited.
• [Standard] — an established industry technical standard.
• [Heuristic] — a production judgment that experienced producers use; not a rule.
• [Policy — dated] — a volatile platform policy verified on the stated date.

1. Decide the production route first

Three routes exist, and they diverge on cost, rights, quality ceiling, and where

you can sell. Pick before touching the manuscript, because the route changes how

you prepare it.

• Human narration — a person performs the book. Highest quality ceiling,

required by some retailers, needs a performer and studio-grade audio.

• Author/producer-driven generative narration — you supply the text to a

TTS system, tune pronunciation and pacing, and master the output yourself.

You control every file and can distribute the finished audio wide.

• Platform auto-narration — a retailer generates the audiobook from your

ebook inside their walled system (e.g., Amazon's Virtual Voice, Google Play

Books auto-narration, Apple Books digital narration). Lowest effort, least

control, and distribution is often tied to that platform.

The rest of this skill mostly serves route 2 (the one where an agent does real

production work) and gives route-3 platform facts in §10.

2. Prepare the manuscript for narration

Print text is written to be *seen*. Narration text must work when *heard*, with

no page to glance back at. Preparing the manuscript is where most audiobook

quality is won or lost, and it is entirely upstream of the voice tool.

Front and back matter — decide, don't default

[Heuristic] Treat each front/back-matter element as a separate short segment and

make an explicit include/omit decision:

• Title page / copyright — usually spoken briefly. Accessibility-focused

production (see §12) narrates copyright, title, and section labels in full;

commercial retail production often compresses them. [Fact] Accessibility

guidance is to begin each section by speaking its title ("Copyright", "Chapter

One"). (NNELS accessibility guidelines, verified 2026-07-10)

• Dedication, epigraph, acknowledgements, also-by lists — short standalone

segments if kept; frequently omitted from commercial audio. Decide per title.

• Opening/closing credits — retail platforms expect them (see §9). Opening

credits state title, author, narrator; closing credits signal finality

("You have been listening to…" then title/author/narrator, then "The End").

Footnotes and endnotes — the hardest call in nonfiction

[Heuristic] A footnote read aloud mid-sentence derails the listener because there

is no visual marker for "this is an aside." For each note, choose one of:

• Fold into the sentence — rewrite so the note's essential fact becomes part

of the spoken prose.

• Read in place, clearly bracketed — introduce it audibly ("In a footnote,

the author adds…") so the listener knows it is an aside.

• Batch at end of chapter/section — collect notes and read them together.
• Drop — citation-only notes (page numbers, ibid., bare URLs) usually add

nothing in audio and are cut.

For scholarly/accessibility editions the default flips toward *including* notes

and bibliographies so the audio carries all the print information. (NNELS, verified 2026-07-10)

Tables, figures, charts, images — rewrite or cut

[Heuristic] A narrator cannot read a chart. Flag everything that depends on the

reader *seeing* it — tables, graphs, figures, image captions, sidebars, complex

formatting. For each: extract the essential finding as one or two spoken

sentences ("Table 3 shows sales roughly doubling each year from 2020 to 2024"),

or cut it. This is why platform auto-narration explicitly warns against

image/table-heavy books and cookbooks/coloring books being unsuitable. ([Amazon

KDP Virtual Voice eligibility](https://kdp.amazon.com/en_US/help/topic/GJSXT4GZLP4PL62B),

verified 2026-07-10)

Inline text that must be spoken out

Build a pre-pass that resolves anything ambiguous when voiced:

• Numbers — "$1,200" → "twelve hundred dollars" or "one thousand two hundred

dollars" (pick per context); "1990s" → "nineteen nineties"; "III" → "the

third". TTS number handling is inconsistent; normalize deliberately.

• Abbreviations/acronyms — decide spell-out vs. say-as-word ("NASA" as a

word; "e.g." → "for example"; "St." → "Saint" or "Street" depending on use).

• URLs and emails — almost always rewritten ("visit the site linked in the

book description") rather than read character by character.

• Symbols — %, &, #, ° must be expanded.

Dialogue attribution

[Heuristic] In print, "she said angrily" tells the reader the tone. In audio the

*performance* should carry the tone, so heavy adverbial tags can feel

redundant — but for **generative narration you often cannot rely on the voice to

act**, so you may need to *keep* attribution the human ear would find obvious, or

add bracketed performance cues the tool can act on where the tool supports them.

Whichever way, make sure every line of dialogue can be attributed by ear: a long

unbroken back-and-forth with no tags leaves the listener unsure who is speaking.

3. Cast the narration

Single narrator vs. multi-voice vs. full cast

[Fact/Heuristic] Two base classes: solo (one voice performs the whole book,

voicing all characters) and multicast (two or more voices). Full cast is the

cinematic extreme — a distinct actor per character, dialogue tags stripped,

sometimes sound design added. (Swift Publishing,

Spines,

verified 2026-07-10)

Decision drivers:

• Point of view. First-person narration usually points to a single

narrator (the listener bonds with one voice = the protagonist). Third-person

ensemble stories tolerate or benefit from multicast. [Heuristic]

• Genre. Nonfiction, memoir, and self-development are overwhelmingly single

narrator — it reads like a lecture or a personal address. SFF and heavily

dialogued fiction gravitate to full/dual cast. [Heuristic, supported by

practitioner consensus above]

• Cost and assembly. [Fact] Full-cast raises cost and, more importantly,

editing burden — you cast, direct, and splice many performers' files together.

(Spines,

verified 2026-07-10)

• Listener preference. [Fact] An Audio Publishers Association figure cited

widely holds that a majority of listeners enjoy the experience more with

distinct character voices — but this is about *differentiation*, not

necessarily separate actors; a skilled solo narrator supplies it too.

(Reported via Spines,

verified 2026-07-10 — treat the exact percentage as secondary.)

For generative production, "full cast" is cheap to attempt (assign different

synthetic voices to characters) but expensive to make *good*: you now have

multiple voices that each must stay consistent, plus the assembly problem. Many

platform auto-narration tools support adding character voices within one book.

(Google Play Books auto-narration,

verified 2026-07-10)

Character differentiation without caricature

[Heuristic] The goal is that a listener can tell who is speaking, not that every

character is a cartoon. For a solo narrator (human or synthetic):

• Differentiate by *pitch, pace, and energy* first, accent last. Accents drift

and offend more easily than a slightly lower, slower register does.

• Keep each character's voice *reproducible*: write down the parameter settings

or the descriptive anchor for each character so Chapter 12's dialogue matches

Chapter 2's. With generative voices this means locking a voice/seed/style per

character and logging it.

• Avoid demographic caricature — do not signal a character's ethnicity, age, or

gender through stereotype. Restraint reads as skill.

4. Hour-scale synthesis: the problems short clips never have

This is the technical core that distinguishes audiobook production from TTS. A

100k-word book is roughly 8–12 hours of audio. (Fish Audio,

verified 2026-07-10)

Voice drift

[Observation, well-documented] Across many hours the timbre, energy, and even

pace of a synthetic voice can shift — the tone that worked in Chapter 1 is subtly

different by Chapter 15 — because chunks are generated independently and random

sampling nudges each one. (Fish Audio,

verified 2026-07-10)

Mitigations:

• Fix the seed / consistency control where the tool exposes one, so sampling

is deterministic across chunks. [Heuristic, tool-dependent]

• Use larger chunks rather than sentence-by-sentence generation; more context

per generation reduces inter-chunk timbre jumps. (tts-audiobook-tool,

Fish Audio,

verified 2026-07-10)

• Anchor voice settings once and reuse them for every chapter — never let the

tool re-pick a voice per session.

• Spot-check across the book — listen to the first minute of Chapter 1, a

middle chapter, and the last chapter back-to-back specifically for drift, not

content.

Chunking strategy

[Heuristic] Chunk on semantic boundaries (sentence/paragraph), not fixed

character counts, so a chunk never cuts mid-clause. Keep chunks as large as the

model reliably handles (a common working figure is on the order of ~80 words per

segment for models that stay accurate at that length; smaller for models that

degrade on long input). (Qwen3 long-form TTS,

verified 2026-07-10) Match chunk size to the specific model's stability, not a

universal number.

Per-chapter architecture

[Heuristic] Generate and store one chapter per file/session. This gives QC

checkpoints and — critically — means fixing Chapter 15 does not force

regenerating the whole book. (tts-audiobook-tool,

Fish Audio,

verified 2026-07-10) It also maps directly onto retail chapterization (§9).

Consistent pacing

[Heuristic] Lock speaking rate globally. Do not speed up dense chapters to save

runtime — inconsistent pace is as jarring as inconsistent timbre. If a passage

needs a different feel (a tense scene, a list), change it deliberately and note

it, don't let it emerge from the chunker.

5. Pronunciation control across a whole book

The signature failure of book-length synthesis: a character named "Siobhan" or a

place named "Worcester" or a term like "Nginx" mispronounced *the same wrong way

every time it appears*. One error becomes forty.

Build a book-wide pronunciation dictionary

[Heuristic, strongly supported] Before generating, scan the manuscript and build

a lexicon of every proper noun, invented term, foreign word, and technical term

with an agreed pronunciation. A tool's pronunciation dictionary / lexicon

applies a fixed pronunciation everywhere the word appears, so you define it once

instead of tagging every instance. (AI Narration Pronunciation Guide,

verified 2026-07-10) Maintain this dictionary as a living artifact for the whole

title (and reuse it across a series so Book 3 pronounces the hero's name like

Book 1).

SSML and phonetic overrides

[Fact] SSML (Speech Synthesis Markup Language) controls pronunciation, pauses,

and emphasis: <phoneme> for a phonetic override, <break> for measured

pauses, <emphasis> for weight, <say-as> for numbers/dates. Phoneme

inventories and supported SSML vary by engine and language. ([Google Play Books

program policies](https://support.google.com/books/partner/answer/10013009),

pronunciation guide,

verified 2026-07-10) Use IPA or the engine's phoneme set for names it gets

wrong; prefer a lexicon entry over inline tags so the fix is global.

Homographs

[Fact] Homographs — same spelling, different sound: "read" (present) vs. "read"

(past), "lead" (verb) vs. "lead" (metal), "tear", "bass", "wind", "live",

"minute", "content". TTS may pick the wrong one from context. ([pronunciation

guide](https://blog.humanizeaudio.com/ai-narration-pronunciation-guide/),

verified 2026-07-10) These cannot be fixed by a single global lexicon entry

(both pronunciations are valid) — they require context-specific overrides at

each occurrence, which is why homographs are a first-class item on the QC pass.

6. Proofing / QC: the listen you cannot skip

[Heuristic, universally emphasized] Generation is not production. You must

listen to the entire audiobook at normal speed — the step most people skip

and the one that catches the errors that produce one-star reviews. ([TTS/AI

narration QC guidance](https://blog.humanizeaudio.com/ai-narration-pronunciation-guide/),

verified 2026-07-10) A skim at 2× hides misreads, clipped words, and drift.

Error taxonomy for the proofing pass

Log every issue by type; each has a different fix:

| Error type | What it sounds like | Typical fix |

|---|---|---|

| Mispronunciation | Name/term said wrong | Lexicon entry; regenerate affected chunk |

| Homograph error | Right word, wrong sound ("lead the team" as metal) | Context-specific phoneme override at that spot |

| Skipped / dropped text | A word, line, or paragraph missing | Re-chunk and regenerate; check for silent SSML/parse failures |

| Inserted / repeated text | A phrase said twice or hallucinated | Regenerate chunk; tighten chunk boundaries |

| Wrong emphasis / stress | Stress on the wrong word, question read flat | SSML emphasis / rephrase; regenerate |

| Pacing fault | Rushed, or unnatural pause mid-clause | Adjust rate / break tags |

| Voice drift | Chapter sounds like a different reader | Re-anchor voice/seed; regenerate chapter |

| Number/date/abbrev misread | "1990s" as "one thousand nine hundred nineties" | Fix in text normalization pre-pass; regenerate |

| Audio defect | Click, breath, clip, glitch, wrong loudness | Fix in mastering (§7), not generation |

Because you generated per chapter (§4), fixes are local: regenerate the affected

chunk or chapter, not the book.

7. Technical delivery specs

[Fact — verified 2026-07-10] Retail audio gates are strict and often

automated: files outside the numeric window are rejected before a human

listens. The widely used ACX/Audible spec is the de facto reference target

and a safe master to hit even for other stores:

• Loudness (RMS): between −23 dB and −18 dB RMS.
• Peak: below −3 dB (true peak), to avoid clipping/encoding distortion.
• Noise floor: below −60 dB RMS. (The hardest spec to meet for home

recordings and the most common cause of rejection.)

• Room tone: 1–5 seconds at the head and tail of every file (max 5s).
• Format: 192 kbps CBR MP3 or higher; 44.1 kHz sample rate.
• Channels: all files the same — all mono *or* all stereo, never mixed.
• File length: each file ≤ 120 minutes.
• One section per file: each file contains exactly one chapter/section.
• Opening credits (title, author, narrator) and closing credits; plus a

retail sample ≤ 5 minutes.

Source: ACX audio submission requirements,

verified 2026-07-10.

[Heuristic] For generative audio, the noise-floor spec is usually *easy* (no mic

hiss) but you still must: normalize loudness to land inside the RMS window,

peak-limit to −3 dB, and add real room tone (a short synthetic near-silence or

low-level tone) so files are not dead-digital-silent at the edges, which some

encoders and QC tools flag. Master per file, then verify every file with a

loudness meter before delivery — one out-of-spec file rejects the whole upload.

8. Chapterization and metadata

[Standard] Deliver one file per chapter/section, named in playback order so

players sort correctly: a chronological number prefix then the section name

(e.g., 01 Opening Credits, 02 Chapter One, 03 Chapter Two). ([APLN /

accessibility production](https://nnels.ca/accessibility-guidelines-audiobook-narrators),

verified 2026-07-10)

[Standard] Embed ID3 tags on each MP3 so the audiobook carries its own

structure: Title = chapter name, Album = book title, Artist =

author/narrator, Track number = playback order. Robust metadata also

improves accessibility and reduces metadata-based rejections. (APLN ID3 intro,

APLN metadata intro,

verified 2026-07-10)

Cover art, title, author, narrator credit, series, and description are set at the

distributor level and must match the ebook/print metadata.

9. Retail platforms and AI-narration policy (verify before you build)

**Policies here are volatile and differ sharply by platform. All verified

2026-07-10 — re-verify at production time.** AI-narration handling ranges from

*banned* to *required-to-disclose* to *the platform generates it for you*.

Audible / ACX — human narration only, with a narrator-consent AI exception

[Policy — verified 2026-07-10] ACX requires human narration; unauthorized

text-to-speech / AI narration is not permitted for standard submissions.

(ACX requirements)

The exception is the Narrator Voice Replica beta (launched July 9, 2025,

US-only): a *narrator* creates an AI replica of their own voice, auditions

and is selected like a human, and edits the output for pronunciation and pacing.

Audible will not use a narrator's replica for any title without approval; titles

using a replica are labeled; compensation can be per-finished-hour, royalty

share, or a hybrid. (ACX blog: Narrator Voice Replicas)

Implication: you cannot upload a generic AI-narrated file to ACX; the AI path

runs through a consenting narrator.

Amazon KDP "Virtual Voice" — Amazon generates it (separate from ACX)

[Policy — verified 2026-07-10] A separate Amazon program (beta, often

invite-based) that generates an AI audiobook from an eligible Kindle ebook.

Eligibility: ebook live ≥7 days, has a table of contents, English primary

language, no existing audiobook, roughly < ~240k words / ~26 hours, and

suitable for audio (cookbooks/coloring books excluded). Choose from a set of

voices; list price $3.99–$14.99; distributed where Audible audiobooks are

sold. (KDP Virtual Voice eligibility,

getting started)

Spotify (via Spotify for Authors) — AI allowed, must disclose

[Policy — verified 2026-07-10] Spotify accepts digital-voice (AI) narration; the

author checks "This audiobook uses digital voice narration," and Spotify appends

a disclosure sentence to the description. It accepts digital narration from

providers such as Google Play Books, ElevenLabs, and others. Note: it does not

share digital-voice titles to referral partners. ([Spotify digital voice

narration](https://support.spotify.com/us/authors/article/digital-voice-narration/))

Findaway Voices → Voices by INaudio — wide distribution, AI allowed with disclosure

[Policy — verified 2026-07-10] **Findaway Voices by Spotify ceased August 1,

2025.** Third-party (non-Spotify) distribution and the self-publishing business

were reacquired by Findaway's co-founders and relaunched as the independent

Voices by INaudio; the old Findaway URL redirects there and logins carried

over. INaudio distributes finished audiobooks to 30+ retailers/libraries

(Audible, Apple Books, Spotify, Google Play, etc.) and takes ~20% of net after

retailers' cut; AI narration is allowed if disclosed. Spotify uploads now go

through Spotify for Authors directly. (Jane Friedman: Findaway as INaudio,

Self-Publishing Advice)

Google Play Books — auto-narration (platform-generated AI)

[Policy — verified 2026-07-10] Google generates the audiobook from your EPUB.

You must own audiobook rights and have the ebook live on Google Play. Supported

input languages include English, Spanish, German, French, Hindi, and Brazilian

Portuguese; 50+ voices; you can add character voices, edit speed, and fix

pronunciation (suggested, phonetic, or by recording the word). Publisher revenue

share ~52%; you may download the files and sell wide, but if it is for sale

elsewhere it must also be on Google Play, and the Google price must not exceed

the price elsewhere. (Google auto-narration,

program policies)

Apple Books — digital narration (platform-generated AI)

[Policy — verified 2026-07-10] Apple produces a digitally narrated audiobook from

a reflowable English ebook that is live on Apple Books, in supported

categories (fiction, romance, mystery & thriller, SFF, nonfiction,

self-development; erotica excluded). Apple's pipeline combines speech synthesis

with linguists, QC specialists, and audio engineers; access is via approved

partners (e.g., Draft2Digital for indie authors, Ingram CoreSource / PublishDrive

for publishers); free; production/QC takes roughly one to two months. You keep

audiobook rights and can produce other versions. ([Apple Books digital

narration](https://authors.apple.com/support/4519-digital-narration-audiobooks),

get started)

Route implication

[Heuristic] If you want an AI audiobook on Audible/Amazon, your realistic

paths are Amazon's Virtual Voice or a consenting narrator's ACX voice replica —

not a self-made AI file. If you want to self-produce AI audio and go wide,

master to ACX specs, disclose AI narration, and distribute through a

wide-distribution aggregator (e.g., INaudio) plus Spotify for Authors — but note

Audible/ACX will not take a generic AI file. Platform-generated routes (Google,

Apple) are lowest effort but keep you inside their pipeline and pricing rules.

10. Rights and consent

[Fact] Text rights and narration rights are separate. The author holds

copyright in the words; the narrator holds a separate performance right in the

recorded performance. Owning the book does not grant rights to a performance of

it, and you must actually hold the audio rights for the title (platform

auto-narration programs require you to attest this and exclude public-domain-only

claims where they require you to own rights). (AI voice cloning legal issues,

Apple,

Google policies,

verified 2026-07-10)

[Fact] Voice cloning requires the voice owner's explicit consent.

Right-of-publicity law protects a person's voice identity from unauthorized

commercial use; cloning a specific narrator or a recognizable voice without

written permission is a legal exposure, and industry practice (e.g., SAG-AFTRA

terms) requires written consent and compensation. Watch licensing fine print

that quietly claims "derivative uses" including model training. ([AI voice

cloning legal issues](https://editorialge.com/ai-audiobook-narration-legality),

Authors Guild on Findaway/Spotify terms,

verified 2026-07-10)

[Heuristic] Apply the "three C's": consent, control, compensation — a voice

is only ethically and legally safe to synthesize when its owner agreed, retains

control over which projects use it, and is paid. For a generic library TTS

voice, your safety comes from the tool's license granting commercial audiobook

use; read that license for scope (commercial use, audiobook distribution,

whether output is yours). Never clone a real person's voice — including a

celebrity narrator's "style" — without documented permission.

11. Accessibility framing

[Heuristic/Fact] Audiobooks are a primary reading format for people with print

disabilities, and accessibility-oriented production has *stricter* completeness

norms than commercial retail: narrate section titles, include footnotes /

endnotes / bibliographies rather than cutting them, and give every section its

own numbered file with full metadata so a print-disabled listener can navigate

the book the way a sighted reader navigates pages. (NNELS guidelines,

AccessiblePublishing.ca,

verified 2026-07-10) When a title's purpose is access (library, education,

public-interest), bias every "include vs. omit" call in §2 toward *include*, and

keep chapterization/metadata (§8) rigorous — it is the navigation layer.

12. End-to-end example (labeled example — not a required formula)

Intent: Self-produce an AI-narrated audiobook of a 95,000-word first-person

memoir with light footnotes and distribute wide.

• Route: Route 2 (self-produced generative). Because Audible/ACX won't take

a generic AI file, plan wide distribution via an aggregator + Spotify for

Authors, with AI narration disclosed.

• Manuscript prep: First-person memoir → single narrator. Convert the ~15

citation footnotes: drop 9 bare-citation notes, fold 4 into sentences, read 2

interesting ones in-line with an audible cue. Normalize numbers/dates,

expand abbreviations, rewrite the one table into two spoken sentences. Write

opening + closing credits.

• Pronunciation dictionary: Scan for proper nouns — the author's hometown

"Beaufort" (BYOO-furt, not BOH-fort), two family surnames, one foreign

phrase. Add lexicon entries. Flag homographs ("read", "tear", "live") for

the QC pass since context decides them.

• Voice + consistency: Pick one library voice licensed for commercial

audiobook use. Fix the seed, set a global speaking rate, generate **one file

per chapter**, and log the exact voice settings.

• QC: Full listen at 1×. Log by the §6 taxonomy: two homograph errors

("live" as adjective, "tear" as crying) fixed with per-spot overrides; one

dropped sentence regenerated; one chapter drifting brighter re-anchored to

the seed and regenerated.

• Master: Per file — normalize to ~−20 dB RMS, peak-limit to −3 dB, add 1s

room tone head/tail, export 192 kbps CBR MP3 @ 44.1 kHz, all mono. Verify

every file with a loudness meter.

• Chapterize + metadata: Files 01 Opening Credits … `NN Closing

Credits`; ID3 Title/Album/Artist/Track on each.

• Rights + disclosure: Confirm audiobook rights held; confirm the voice

license covers commercial audiobook distribution; set the "digital voice

narration" disclosure flag at every distributor that requires it.

Expected result: A spec-compliant, chapterized, disclosed AI audiobook

accepted wide. Likely failure modes: a mispronounced name that slipped the

lexicon, one out-of-RMS file rejecting the upload, or forgetting the disclosure

flag. Variation: an ensemble third-person novel would push toward multicast

(one consistent voice per major character, each with its own logged settings and

its own drift check), and a scholarly nonfiction title would push toward

*including* footnotes and full section-title narration.

Sources (verified 2026-07-10)

• ACX audio submission requirements — https://help.acx.com/s/article/what-are-the-acx-audio-submission-requirements
• ACX Narrator Voice Replicas beta (July 9, 2025) — https://www.acx.com/mp/blog/now-in-beta-narrator-voice-replicas-on-acx
• Amazon KDP Virtual Voice eligibility — https://kdp.amazon.com/en_US/help/topic/GJSXT4GZLP4PL62B
• Amazon KDP Virtual Voice getting started — https://kdp.amazon.com/en_US/help/topic/GFAQU3LUEHCRB8KD
• Spotify digital voice narration — https://support.spotify.com/us/authors/article/digital-voice-narration/
• Google Play Books auto-narration — https://play.google.com/books/publish/autonarrated/
• Google Play Books auto-narrated program policies — https://support.google.com/books/partner/answer/10013009
• Apple Books digital narration — https://authors.apple.com/support/4519-digital-narration-audiobooks
• Apple Books get started with digital narration — https://authors.apple.com/support/4973-get-started-digital-narration
• Findaway Voices → Voices by INaudio transition (Jane Friedman) — https://janefriedman.com/what-authors-need-to-know-about-the-return-of-findaway-as-inaudio/
• Spotify ends Findaway Voices (ALLi/SelfPublishingAdvice) — https://selfpublishingadvice.org/spotify-ends-findaway-voices/
• Long-form TTS voice consistency / drift & chunking (Fish Audio) — https://fish.audio/blog/best-text-to-speech-for-audiobooks-2026/
• Long-form TTS chunking / per-chapter architecture (tts-audiobook-tool) — https://github.com/zeropointnine/tts-audiobook-tool
• Qwen3 long-form TTS (chunk sizing) — https://medium.com/data-science-collective/high-quality-long-form-tts-with-qwen3-open-weight-models-cdd6e3d00df0
• AI narration pronunciation, SSML, homographs, QC — https://blog.humanizeaudio.com/ai-narration-pronunciation-guide/
• Single vs full cast narration (Swift Publishing) — https://swiftbookpublishing.co.uk/audiobook-narration-styles/
• Pros/cons full cast vs single narrator (Spines) — https://spines.com/pros-and-cons-full-cast-audiobooks-vs-single-narrator/
• Accessibility guidelines for narrators (NNELS) — https://nnels.ca/accessibility-guidelines-audiobook-narrators
• ID3 tags in audiobooks (APLN) — https://apln.ca/introduction-to-id3-tags-in-audiobooks/
• Audiobook metadata intro (APLN) — https://apln.ca/introduction-to-audiobook-metadata/
• AI voice cloning legal issues / narration vs text rights — https://editorialge.com/ai-voice-cloning-for-audiobook-narration-legal-issues/
• Authors Guild on Findaway/Spotify audiobook terms — https://authorsguild.org/news/response-to-findaway-spotify-audiobook-terms-of-use/

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