Hindi has a few pronunciation features that are genuinely harder for any AI vocal model than plain, unambiguous text — not because the model is bad at Hindi generally, but because these specific patterns carry information that plain script does not always make explicit. Knowing which category a mispronounced word falls into makes it much faster to fix.
The specific Hindi trouble spots
A handful of patterns account for most Hindi mispronunciations in AI-generated vocals.
- Conjunct consonants — clusters like क्ष (ksh), ज्ञ (gy/jn) or त्र (tr) combine two consonant sounds into one written unit, and an uncommon or complex conjunct is more likely to be guessed at than a simple syllable the model has seen constantly.
- Nasalization (chandrabindu / anusvara) — the nasal marker above a vowel (ँ, ं) changes the sound meaningfully, e.g. हँस versus हस. It is a small mark that is easy to lose in fast singing or if the source text drops it.
- Retroflex vs. dental consonants — Hindi distinguishes retroflex ट, ड from dental त, द, a distinction English speakers often collapse and one AI models can occasionally soften in a way that shifts the word.
- English loanwords inside Hindi lines — a word like 'style' or 'love' sitting in an otherwise Hindi line can get pulled toward Hindi-style pronunciation rules or vice versa, depending on context.
- Schwa deletion — Hindi drops the inherent 'a' vowel in specific positions (e.g. 'karm' not 'karama'), and a model can occasionally sing the full, undeleted form, which sounds distinctly off to a native ear even though it is not 'wrong' in a simple sense.
Fixes for each category
Once you know which pattern is causing the problem, the fix is usually direct.
- For a mishandled conjunct — try writing the word with the conjunct spelled out more explicitly, or as a common alternate spelling if one exists.
- For lost nasalization — double-check the chandrabindu or anusvara is actually present in your source text; a dropped mark is a common, easy-to-miss cause.
- For a retroflex/dental mix-up — this is usually a subtle vocal issue rather than a spelling one; regenerating the line as a variation often resolves it since generation has some natural variation pass to pass.
- For an awkward English loanword — try writing it phonetically in Devanagari to match how it is actually said in the Hindi sentence, rather than leaving it in Roman script mid-line.
Fixing it with Auto-Fix, without redoing the song
Open the song in Studio's Lyrics tool and run Auto-Fix pronunciation. It listens to the finished song, transcribes exactly what was sung, compares that transcript word-by-word against your original lyrics, and re-records only the spans that do not match — same melody, corrected words, and the rest of the song untouched. It takes about 5-10 minutes and costs 20 credits on Pro and Creator plans.
If you want to fix one specific line yourself instead, the manual route costs 3 credits and is available on the free tier: select the passage on the waveform, retype the corrected words, and choose how much freedom the AI gets to change the delivery, from keep-the-melody to a fuller rewrite.
When it is not really a pronunciation bug
Occasionally what sounds like a mispronunciation is the model choosing a legitimate but unintended reading of genuinely ambiguous Roman-script text — 'hai' read with a different vowel length than you meant, for instance. In that case, switching that word to Devanagari, which removes the ambiguity, is usually faster than trying to 'fix' a pronunciation that was not technically wrong.