AI Voice Pronunciation Guide: Fix Names, Acronyms, and Numbers

An AI voice pronunciation guide should start with one rule: do not send display text directly to text-to-speech and hope it reads correctly. Create a spoken script first. Expand ambiguous numbers, decide whether each acronym is spoken or spelled, record the approved pronunciation of every name, and test those tokens inside their final sentences. Use provider dictionaries or phoneme rules for recurring terms; use plain-language rewrites for one-off corrections. Then regenerate only the failed line.

You can apply this workflow in Oakgen's AI audio workspace with ElevenLabs or a MiniMax cloned voice, depending on the controls and voice identity your project needs.

The quick fix table

If the script has more than a few high-risk terms, do not fix them ad hoc. Build a reusable pronunciation sheet before the first generation.

Who needs this workflow

This is for anyone whose audio cannot afford a small verbal error:

• product marketers reading brand names, prices, and model numbers;
• course teams using technical vocabulary across many lessons;
• podcasters citing people, places, and research;
• SaaS teams narrating feature releases and API tutorials;
• localization teams moving one script across accents and languages;
• agencies producing many ad variants from one approved brief.

A misread dosage, price, or legal entity changes meaning. Treat pronunciation as content QA, not an aesthetic preference.

Research note and provider limits

This guide was checked against current ElevenLabs and MiniMax documentation on August 13, 2026, plus Oakgen's currently exposed audio controls. It is a workflow guide, not a claim that every provider supports the same markup.

ElevenLabs documents project pronunciation dictionaries with alias substitutions and, on compatible models, IPA or CMU phoneme rules. MiniMax documents language boosting plus speed, pitch, and volume controls, but its public speech API overview does not describe an equivalent pronunciation dictionary. Plain-language script normalization works across both because it changes the input rather than depending on provider-specific markup.

For broader model selection, read ElevenLabs vs MiniMax and our AI voice cloning and text-to-speech guide.

Step 1: keep display text and spoken text separate

The text on a screen and the text a voice should read are not always the same asset.

Display text favors brevity: $1.05, v2.6, 03/04/26, 5 mg, oakgen.ai. Spoken text needs meaning: “one dollar and five cents,” “version two point six,” an explicit date, “five milligrams,” and the approved way to say the domain.

Create two columns in the working document: display text and spoken text. Save 15% on v2.6 can become Save fifteen percent on version two point six; a domain can be written as its approved brand reading plus dot A I slash docs. Do not silently overwrite the source copy. The editor may need the visual form for captions while the TTS system needs the spoken form for audio.

Step 2: build a high-risk token list

Before generation, scan the script for tokens in these groups:

1. names of people, places, brands, and products;
2. acronyms, initialisms, and abbreviations;
3. prices, percentages, dates, times, ranges, and phone numbers;
4. versions, URLs, file extensions, units, and formulas;
5. homographs such as “lead,” “read,” “record,” and “live”;
6. words from a second language;
7. words that change meaning when stress moves.

This list becomes the pronunciation manifest for the project. Add an owner, an approved reading, and one test sentence for every high-risk token.

This lets a subject-matter expert approve terms without listening to the full draft.

Step 3: fix names with evidence, not guesswork

The best source for a person's name is that person. For a brand, use the brand's own pronunciation. For a place, use a reliable local or institutional source.

Store the exact written form, plain-language sound guide, stressed syllable, and one sentence containing the name.

For example, a made-up name might be stored as Mariven — MAIR-ih-ven — stress MAIR. The sound guide is not a universal phonetic standard; it is a practical bridge for an editor. If the provider supports IPA or CMU and your team knows how to review it, add the formal phoneme representation too.

Test first and last names together. ElevenLabs' best-practices documentation notes that phoneme tags work on individual words, so a full name may require a rule for each part. Also test possessives and plural forms because the added sound can change the rhythm.

Step 4: classify every acronym

An acronym list usually contains three different things:

Spell initialisms. API, CEO, and URL are commonly read letter by letter in many contexts. Write spaces, separators, or a pronunciation alias so the model does not merge them. Listen at the final speed; fast delivery can blur adjacent letters.

Say established acronyms as words. A plain-language alias can lock that reading when the model tries to spell it.

Expand abbreviations when clarity matters. approx., dept., or a domain-specific shorthand may be clearer when expanded. In training material, say the full phrase once and the shortened form later.

Context decides. SQL is a classic example because teams use more than one accepted pronunciation. Your job is not to choose the internet's favorite. Your job is to match the product team's approved style.

Create a project acronym table:

Step 5: normalize numbers before generation

Numbers are dangerous because the written form does not contain enough intent.

Prices and decimals. $1.05 might be read as “one point zero five dollars” when the desired line is “one dollar and five cents.” Write the desired speech. Do the same for large values where “one hundred and five” versus “one oh five” changes the register.

Dates and time. 03/04/26 changes meaning by locale, so replace it with an explicit date. 3:05 can mean “three oh five,” “five past three,” or a duration. Add the context the listener needs.

Versions and ranges. Write version two point six, not just 2.6. Render 5–10 as “five to ten,” “five through ten,” or another approved phrase. A minus sign, en dash, and hyphen can look similar but mean different things.

Units and codes. Expand symbols when safety or clarity matters: mg, mm, m, and MB are not interchangeable. Decide whether phone or account digits are grouped or individual, and never include sensitive production credentials in third-party TTS input.

Step 6: handle homographs with sentence rewrites

Homographs share spelling but change pronunciation by meaning. Examples include:

• “record” as a noun versus a verb;
• “live” as an adjective versus a verb;
• “lead” as a metal versus the act of guiding;
• “read” in present versus past tense.

The cleanest fix is often a sentence rewrite that removes ambiguity. “Record the session” can become “Start recording the session.” “The live event” can become “The event is happening now.”

If the exact wording must remain, use a provider-specific alias or phoneme rule. Do not rely on capital letters as a permanent fix; typography may influence one render but is not a maintained pronunciation system.

Step 7: control multilingual and code-switched lines

ElevenLabs explains that text drives language detection while the selected voice influences accent and pronunciation. MiniMax exposes language boosting. Those controls help, but a code-switched sentence can still confuse rhythm or accent.

Use this order:

1. Select a voice suited to the dominant language and accent.
2. Set the provider's language control where available.
3. Split sustained language changes into separate segments.
4. Keep borrowed brand terms in the reading approved for that market.
5. Have a native reviewer approve the final audio.

Do not transliterate an entire language casually. Transliteration can remove distinctions a native script preserves. Use it only when the pronunciation has been explicitly approved.

Step 8: use the right correction level

There are four levels of intervention. Start with the lightest one that remains repeatable.

1. Plain-language rewrite: best for a one-off number, date, or abbreviation. It works across providers and is visible to editors.
2. Alias rule: best for a recurring brand term or acronym. ElevenLabs documents aliases in pronunciation dictionaries, including for models that do not use phoneme tags.
3. Phoneme rule: best for a precise recurring pronunciation when the model supports it and the team can review IPA or CMU. Check model compatibility first.
4. Sentence rewrite or voice change: use this when the term remains unstable. A different sentence can add context; a native voice may solve an accent problem markup cannot.

Inside Oakgen, start with the voice generator walkthrough, choose the voice and model for the job, then run a short token test before producing the full script.

The pronunciation preflight scorecard

Copy this into a brief or spreadsheet. It is designed to catch expensive mistakes before the full render.

Add a “failed take” column if the project repeats. Patterns become obvious: one voice may struggle with initials at high speed, while another may drift on mixed-language lines.

A repair workflow that avoids full rerenders

When one word fails, do not immediately regenerate ten minutes of audio.

1. Duplicate the failing sentence into a repair script.
2. Keep the same voice, model, and neutral settings.
3. Apply one correction: rewrite, alias, phoneme, or context.
4. Generate two or three candidates.
5. Compare identity, pace, and room tone with the lines before and after.
6. Replace only the failed sentence in the edit.
7. Save the winning rule in the pronunciation manifest.

Generate at sentence or short-paragraph boundaries from the start. That gives the editor a natural splice point and limits repair cost.

Common AI voice pronunciation mistakes

• Fixing delivery before meaning: stability, style, or speed will not resolve an ambiguous date. Normalize meaning first.
• Using hyphens everywhere: they can create unnatural pauses. Use a maintained alias or approved spoken rewrite for important terms.
• Testing words in isolation: surrounding text changes stress and timing. The final sentence is the test unit.
• Forgetting captions: spoken and visible text can differ by design, but they must communicate the same meaning.
• Mixing systems without records: put every rewrite, alias, and phoneme rule in one manifest with an owner and date.
• Skipping regional review: language support does not guarantee the expected local accent. Use a native reviewer for public-facing localization.

Frequently asked questions

How do I make an AI voice pronounce a name correctly?

Confirm the intended pronunciation with the person or brand, write a plain-language sound guide, mark the stressed syllable, and test the full sentence. For repeat use, save an alias or compatible phoneme rule in a pronunciation dictionary.

How should AI text-to-speech read acronyms?

Classify each item before generation: spell initialisms letter by letter, read established acronyms as words, and expand abbreviations when listeners need the meaning. Do not rely on capitalization alone.

Why does TTS pronounce the same word differently in another sentence?

Text-to-speech models use surrounding context, punctuation, language cues, and voice characteristics. A word that works in isolation can change inside a sentence, so pronunciation QA must test the final line.

Can punctuation fix AI voice pronunciation?

Punctuation can improve phrasing and pauses, but it is not a reliable pronunciation system. Use an approved spoken rewrite, alias, or phoneme rule for important terms, then use punctuation for delivery.

Should I write numbers as digits or words for text-to-speech?

Use digits in the source document if people need them visually, but convert ambiguous numbers into approved spoken words in the TTS script. Prices, dates, versions, units, phone numbers, and ranges need explicit treatment.

Does Oakgen support pronunciation control?

Oakgen's audio workspace exposes provider-specific voice and model controls. For strict terminology, prepare a spoken script before generation and choose the provider workflow that offers the correction method your project needs.

Sources and further reading

• ElevenLabs pronunciation dictionary guide
• ElevenLabs text-to-speech best practices
• ElevenLabs supported-language guidance
• MiniMax speech API overview
• Best AI text-to-speech tools
• Free ElevenLabs alternatives