How to fix TTS pronunciation errors
Mispronounced brand names destroy credibility faster than bad visuals. TTS engines guess from spelling — and Hindi, Urdu, and English mixes give them plenty to guess wrong. A systematic pronunciation pass catches 90% of issues before publish.
This guide documents test-isolate-fix loops: phonetic spellings, hyphen stress, glossary maintenance, and QA checklists for long scripts. Keep a running "hard words" doc and test each addition in Cosette before full generate.
The isolate-test method
Never debug pronunciation inside a 2,000-word export. Paste the problem word in a short sentence — "Welcome to Cosette AI" — iterate spelling until correct, then merge fix into master script.
Phonetic spelling strategies
Latin phonetics for English names in Urdu scripts; Devanagari approximations for foreign brands; hyphenate compound terms ("You-Tube" rarely helps — prefer official brand spelling your engine knows).
Language-mix pitfalls
Hinglish sentences switch scripts mid-line — mark pause commas around English tokens. See Hinglish guide.
Numbers, dates, currency
₹499 vs "four ninety-nine rupees" — choose spoken form in script. Years like 2026 may read as "two thousand twenty-six" or "twenty twenty-six" depending on engine — test once, standardize.
Acronyms and abbreviations
FBI as letters vs acronym; expand on first use in educational content. IIT-JEE needs hyphen pause for some engines.
Building a project glossary
Columns: term, approved spelling, test sentence, voice ID, date verified. Share with writers before draft.
When to swap voice or speed
Persistent failures on one voice may clear on another model — but spelling fix beats voice hopping. Slow 0.95× helps dense terms.
Pre-publish QA ritual
- Full listen at 1× speed
- Spot-check at 1.25× (Shorts pace)
- Second pair of ears on names
- Archive script version with audio hash
Pair with natural voice tips for flow after fixes.
Voice selection in production
Cast voice like hiring an actor: record three candidates on the same paragraph, blind-test with five listeners, pick winner by score not gut. Document choice in style guide with forbidden alternatives to prevent drift.
Seasonal refreshes (holiday ads, exam pushes) can keep the same voice — consistency builds brand equity. Swap voice only for deliberate spin-offs labeled as such.
When A/B testing hooks, change script not voice — otherwise you confound variables.
Key takeaways for clean pronunciation
Isolate problem words in test sentences. Build a project glossary. Fix spelling before regenerating entire scripts. Second listener catches what authors miss — especially for Urdu and Hindi loanwords.
Building a pronunciation glossary
Columns: term, approved spelling, test sentence, voice ID, verified date. Share with all writers before draft. Update when brands rebrand.
Regression testing after engine updates
When TTS provider updates voices, re-run glossary test sentences. Regression fixes are faster than discovering errors in published video.
Building a pronunciation lab session
Before every batch generate, open a scratch document with five lines: your hardest proper noun, a number with currency, an English brand inside Hindi, a question sentence, and a acronym. Generate each line alone in Cosette. Failures get a glossary entry before they infect a ten-minute script.
Phonetic rewrites work when they are consistent: if you spell Mumbai one way in episode 1, keep that spelling in episode 40. Hyphenation guides stress for compound terms — “text-to-speech” read as one unit may need spaces or commas in Devanagari contexts.
Team workflow for clean audio
Assign a “second listen” role on every publish — not the author. Authors hear what they meant; fresh ears catch misread acronyms. Log fixes in pronunciation.md with date and voice ID. When a provider updates models quarterly, rerun the five-line lab — regressions are common on names, not on common words.
Numbers, dates, and currency in South Asian scripts
Decide whether narration says “five crore” or digits — engines vary. Test rupee amounts, lakh/crore phrasing, and Gregorian versus fiscal year labels in isolation. Hindi and Urdu scripts may need Latin digits inside Devanagari sentences for clarity.
Document the house style in your glossary so writers do not mix formats across episodes — inconsistency sounds like sloppy production even when each line is technically correct.
Loanwords from English in Hindi scripts
Product names and APIs often stay Latin — surround them with Hindi grammar in Devanagari and test stress on the boundary syllable. Writers sometimes italicize English in docs; remove formatting artifacts before paste into TTS — asterisks and underscores become silence or glitches in some engines.
Voice-specific quirks
Same spelling may work on one avatar and fail on another — glossary entries should note voice ID. When switching providers, rerun the full glossary; migrations are when most pronunciation debt surfaces.
Subtitle parity checks
When you fix pronunciation in audio, update captions the same day — mismatched captions confuse SEO and deaf viewers. Treat script, audio, and SRT as one versioned bundle.
On-screen text alignment
When video burns key terms on screen, spoken and written forms should match — TTS may read a phonetic spelling while graphics show brand orthography. Align both after glossary approval.
Closing production checklist
Before batch export, rerun your five-line pronunciation lab, confirm glossary entries match on-screen spellings, and assign a second listener for the full track. Log voice ID and date in the project readme. When platforms or clients audit originality, glossary discipline proves you run QA, not one-click generation. Store regression test results after each TTS engine update — fix drift before it reaches published video. Clean pronunciation is cumulative: small tests prevent large embarrassments on brand names and acronyms.
One habit to keep
Document voice ID, script version, and export date in every project folder before upload. Future you — and any freelancer — ship faster when settings are not guesswork. That habit prevents most inconsistent TTS output across a series.
Frequently asked questions
Why does TTS misread names?
Models predict from training spelling — rare names lack data.
Should I use IPA notation?
Only if engine supports it — phonetic plain spelling usually works.
Do hyphens help?
Sometimes for stress; test — over-hyphenation breaks flow.
Hindi Devanagari fixes?
Rephrase sentence or use alternate native spelling of loanwords.
Re-generate whole script after one fix?
No — patch sentence only to save time.