Troubleshooting · 6 min read

Why Are My AI Lyrics Mispronounced?

Published 25 February 2026

Short answer

Mispronunciation usually happens when the model was not built for your language — English-centric tools mangle Hindi and regional words. Fixes include using a model tuned for your language (Autunes uses Zori5 Turbo for Indian languages), trying Devanagari vs Roman script, and simplifying tricky spellings phonetically.

If your lyrics come out with the wrong accent or garbled words, the model is usually the cause — not your prompt.

Use the right model

English-centric tools struggle with Hindi, Punjabi and regional languages. Autunes uses Zori5 Turbo, tuned for Indian-language vocals, which pronounces them authentically.

Other fixes

Try switching between Devanagari and Roman script, spell tricky words the way they should sound, and keep lines clear. Small phonetic tweaks often fix a stubborn word.

  • Use a language-tuned model (Zori5 Turbo).
  • Try Devanagari or Roman script.
  • Spell tricky words phonetically.

Script choice matters more than the prompt

The biggest single lever on pronunciation is what script you paste. Native scripts encode vowel length and aspiration explicitly; Roman transliteration discards both and forces the model to guess. 'bhala' and 'bala' are nearly identical in Roman and completely different in Devanagari.

If a specific word keeps landing wrong, regenerate before you rewrite. The model takes a different sampling path each time, and a word that came out wrong on one take frequently comes out right on the next with no change to the input at all.

  • Paste the native script, not Roman transliteration.
  • Keep diacritics and nukta dots — they change the word.
  • Regenerate before rewriting; the same prompt samples differently.

Try it yourself

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Frequently asked questions

Why does Suno mispronounce Hindi?

Its models are English-centric. For authentic Hindi, use Autunes (Zori5 Turbo).

Does script choice matter?

Sometimes — switching between Devanagari and Roman script can fix a mispronounced word.

Why is the same word pronounced correctly once and wrongly the next time?

Because generation is probabilistic. Each take samples a different path, so borderline words can land either way. Regenerating is the cheapest fix.

Does the model handle aspirated consonants?

Yes for the languages it natively supports, provided you write in the native script. In Roman transliteration the aspiration is not in the input at all, so it cannot be reproduced reliably.

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