Nothing breaks the illusion of AI narration faster than a mispronounced brand name. Your company is "Zyxel" (zy-KSEL), the voice says "ZIX-el" — and every listener winces. Mispronunciations are the #1 quality complaint about TTS, and they are almost always fixable.
This guide shows how to make TTS pronounce words correctly: quick phonetic-spelling tricks for one-off fixes, SSML for precise control, and pronunciation libraries for brand-wide consistency. From product names to medical jargon, you will get every word right.
Key Takeaways
- Phonetic respelling ("kuh-TAR" for Qatar) fixes 80% of pronunciation problems in seconds.
- SSML phoneme tags give exact IPA-level control for stubborn words.
- Build a pronunciation library/dictionary so fixes apply consistently across all content.
- Always test pronunciations in full sentences — isolated words can mislead.
- Proof-listen specifically for names and terms; they are where errors hide.
The Quick Fix: Phonetic Respelling
The fastest method — rewrite the word as it sounds:
- Qatar → "kuh-TAR"
- Nguyen → "nWIN" or "goo-YEN" (pick your preferred)
- QSR brand "Zyxel" → "zy-KSEL"
- GIF → "ghif" or "jif" (choose your camp)
- Ubuntu → "oo-BOON-too"
- Acai → "ah-sah-EE"
Technique tips:
- Use CAPITALS for stressed syllables — most engines stress capitalized syllables naturally.
- Hyphenate syllables to force breaks: "ex-ASS-er-bate" for exacerbate.
- Simplify consonant clusters the engine stumbles on: "Worcestershire" → "WOOS-ter-sheer."
- For acronyms, choose: spell out ("F-B-I") or pronounce as word ("NASA" → "NASS-uh").
Limits: respelling is approximate — fine for narration, insufficient for broadcast-exact needs. And respelled text looks wrong if anyone reads the script, so keep a clean master script plus a TTS-ready version.
Precise Control: SSML Phonemes
When respelling is not exact enough, SSML delivers surgical precision:
<speak>
Our product, <phoneme alphabet="ipa" ph="zaɪkˈsɛl">Zyxel</phoneme>,
launches <say-as interpret-as="date" format="mdy">10/17/2026</say-as>.
</speak>
How to get IPA transcriptions:
- Wiktionary lists IPA for most words and names.
- For brand/invented words, transcribe your intended pronunciation using an IPA chart.
- Test iteratively: generate, listen, adjust the transcription.
say-as for structured content:
| Content | SSML | Result |
|---|---|---|
| Date | "October 17th, 2026" | |
| Acronym | "F B I" | |
| Number | "forty-two" | |
| Phone | Digit-grouped reading | |
| Time | "three thirty PM" |
Most TTS studios now wrap these in UI controls — learn the concepts here, then use buttons where available.
Brand-Wide Consistency: Pronunciation Libraries
One-off fixes do not scale. For brands, courses, and series, build a pronunciation library:
1. Inventory problem words. After your first full proof-listen, list every mispronounced term: brand names, product lines, founder names, jargon, partner companies.
2. Define canonical pronunciations. Get sign-off from brand/marketing — "how do WE say it" is the authority, not dictionaries.
3. Store phonetic + SSML forms. Keep a shared doc or the studio's built-in dictionary: word → respelling → IPA/SSML → example sentence.
4. Apply globally. Good studios apply dictionary entries to all future generations automatically; for manual workflows, find-and-replace the TTS-ready script before generating.
5. Review quarterly. New products and terms arrive constantly; a stale dictionary is a mispronunciation waiting to happen.
Real example: a SaaS company with 40+ feature names cut narration QA time 70% after building their dictionary — the first video took a day of fixes; the fiftieth took none.
Tricky Categories and Solutions
Non-English names in English text. "Saoirse" → "SEER-sha"; "Joaquín" → "wah-KEEN." Decide house style: anglicized or authentic, then stay consistent.
Medical/legal/technical jargon. "Acetaminophen" → "ah-see-tah-MIH-noh-fen." For regulated content, have a subject expert verify every respelling — a wrong drug pronunciation is a liability.
Numbers and units. "5G" → "five G"; "$3.2B" → "three point two billion dollars"; "COVID-19" → "COVID nineteen." Write a style rule once, apply everywhere.
Homographs. "Read" (present/past), "lead" (metal/guide), "bass" (fish/sound) — engines guess from context and often guess wrong. Respelling disambiguates: "reed" vs "red," "leed" vs "led."
Emojis and symbols. Strip them from narration scripts or replace with words ("→" → "leads to"). Most engines skip or garble symbols.
The golden rule: proof-listen at 1x speed with the script in front of you, pen ready. Automated checks catch nothing here — human ears are the QA tool.
Frequently Asked Questions
Why does TTS mispronounce my brand name?
TTS engines apply general pronunciation rules that fail on invented words, unusual spellings, and non-English names. Fix it with phonetic respelling ("kuh-TAR" for Qatar) for quick jobs, SSML phoneme tags for precision, or a pronunciation dictionary for brand-wide consistency.
What is the easiest way to fix TTS pronunciation?
Phonetic respelling: rewrite the word as it sounds using capitals for stressed syllables ("nWIN" for Nguyen). It fixes 80% of problems in seconds with no technical knowledge. For stubborn words, use SSML phoneme tags with IPA notation.
How do I make TTS read acronyms correctly?
Decide per acronym: spell out with
Can I save pronunciations for future projects?
Yes — most TTS studios offer pronunciation libraries/dictionaries where you define a word’s pronunciation once and it applies automatically everywhere. For manual workflows, keep a shared doc of respellings and apply with find-and-replace before generating.
How do I handle foreign names in English narration?
Pick a house style (anglicized vs. authentic pronunciation) and apply it consistently. Respell phonetically ("SEER-sha" for Saoirse), test in full sentences, and store in your pronunciation library. For regulated content, have native speakers verify.
Related Guides
- Text to Speech API Guide for Developers
- How to Write Scripts for AI Voiceover
- ElevenLabs Alternative: Compare Top AI Voice Tools
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