A nearly perfect voiceover can lose credibility when it says a product, name, or acronym wrong. Vois's pronunciation dictionary gives you a repeatable way to catch that error before it reaches an audience.
Or it pronounces your company name like it's never heard of it. Or it reads "LUFS" as a word instead of spelling out the letters. Or it turns "Dr. Mehta" into something unrecognizable.
Every voice system has blind spots. Names, brands, acronyms, technical terminology, and foreign words in English context can break an otherwise natural delivery.
The Vois pronunciation dictionary lets you make an approved spoken form part of the workflow, rather than correcting the same word in every script.
How It Works
The concept is simple: you tell Vois how a word should be pronounced, and it remembers.
Add a rule: "Vois" should be spoken as "Voyce." From that point forward, every time your text contains "Vois," the engine sees "Voyce" instead. The substitution happens before audio generation, automatically every time.
Rules are stored in a local database. They persist across sessions, across projects, across restarts. Add a rule once and forget about it.
Words That Need Rules
Certain categories of words reliably cause problems:
Brand Names
Most brand names are invented words with non-obvious pronunciation. Voice engines have to guess, and the guess can be wrong.
| Brand | TTS Might Say | Rule |
|---|---|---|
| Vois | "Voh-iss" | "Voyce" |
| Canva | "Can-vah" | "Can-vuh" |
| Asana | "Ah-sah-nah" | "Ah-sahn-uh" |
| Figma | "Fig-mah" | "Fig-muh" |
If you're producing content for a specific brand, add their name on day one. It'll save you from catching the mispronunciation after you've already generated 20 minutes of audio.
Character Names in Fiction
Audiobook authors deal with this constantly. Fantasy and sci-fi names are particularly tricky:
| Name | Problem | Rule |
|---|---|---|
| Aethon | "Ay-thon" when you want "Ee-thon" | "Ee-thon" |
| Cthulhu | Anybody's guess | "Kuh-too-loo" |
| Hermione | Often mangled | "Her-my-oh-nee" |
For audiobooks with large casts, you might have dozens of character names that need rules. This is where CSV import becomes essential (more on that below).
Acronyms and Initialisms
TTS engines have to decide: is this an acronym (read as a word) or an initialism (spell out the letters)?
| Term | Common Error | Rule |
|---|---|---|
| LUFS | Read as "luffs" | "L U F S" (spell it out) |
| ASMR | Read as "azmer" | "A S M R" |
| SQL | Read as "sequel" or "S Q L" | Your preference |
| API | Usually correct | Verify first |
| GDPR | Sometimes "guh-dpr" | "G D P R" |
The space-separated letters trick works well: writing "L U F S" in the replacement forces the engine to spell it out letter by letter.
Medical and Legal Terminology
Specialized fields have vocabulary that general TTS models rarely encounter in training data:
| Term | Common Error |
|---|---|
| Dysphagia | Stress on wrong syllable |
| Voir dire | Anglicized incorrectly |
| Amicus curiae | Butchered Latin |
| Ophthalmology | Dropped syllable |
If you're producing medical or legal content regularly, build a domain-specific dictionary. It's an investment that pays off across every future project.
Global vs Project-Specific Rules
Rules come in two scopes:
Global rules apply across every project. Use these for permanent vocabulary, such as your brand name, common acronyms, and frequently used technical terms. These are your "set and forget" rules.
Project-specific rules apply only within a single project. Use these for context-dependent pronunciation, such as character names in a specific audiobook, product names in a specific training series, or jargon relevant to one client.
Most people start with global rules for their most common terms, then add project-specific rules as needed. The two layers do not conflict. Project rules take priority over global rules when both exist for the same word.
The CSV Workflow
Adding rules one at a time works for a handful of terms. If you are building a comprehensive dictionary, such as an audiobook with 40 character names or a medical course with 100 technical terms, use bulk import.
Export your current dictionary as CSV, add new entries in a spreadsheet, and import the updated file. The CSV format is two columns: original word and replacement.
original,replacement
Vois,Voyce
LUFS,L U F S
ASMR,A S M R
Mehta,May-tah
This also makes dictionaries portable. Export from one Vois installation, share the CSV with a colleague, import on their machine. Consistent pronunciation across your team.
Word Matching Details
The dictionary uses whole-word matching. A rule for "Dr" replaces "Dr" but not "Dr" inside "Dragon" or "Dry." This prevents the kind of cascading substitution errors that make dictionary systems unreliable.
The matching algorithm processes longest matches first. If you have rules for both "New York" and "York," the two-word phrase gets priority. This lets you create compound rules without worrying about partial matches breaking them.
Building Your Dictionary Over Time
The best pronunciation dictionaries aren't built in a day. They grow organically:
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Start with known problems. Your brand name, your host's name, your most common acronyms. Add these before your first generation.
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Catch issues during review. When you listen to generated audio and hear a mispronunciation, add a rule immediately. Do not postpone it until the term is easy to forget.
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Import domain vocabularies. If you're entering a new content domain (medical training, legal content, a new game universe), build a starter dictionary from your terminology list before generating anything.
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Export and backup. Periodically export your dictionary as CSV. It represents accumulated knowledge about how your content should sound. Treat it like any other production asset.
The Difference It Makes
A pronunciation dictionary is a quiet production feature, but it makes the difference between audio that is almost right, with jarring mispronunciations breaking the flow, and audio that sounds consistently professional.
The first time your AI voice nails a difficult name that it used to butcher, you'll understand why this feature exists.
Set the rule once, review the rendered line, and carry the approved pronunciation into the next project. Explore the Vois pronunciation dictionary, then get started when you are ready to keep your vocabulary consistent.
The Vois Team