How accurate is Polish speech to text with local Whisper?
Polish is one of the languages where the published numbers line up cleanly. In the Whisper paper itself (arXiv:2212.04356), the large-v2 model scores 5.0% word error rate on Polish Multilingual LibriSpeech and 5.4% on Polish FLEURS. Two different corpora agreeing within half a point is a good sign - it means the figure is about the language, not about which recordings someone picked.
Both of those are clean read speech, so treat them as a floor rather than an expectation. How far the floor sits from real life is documented for Polish specifically: a published comparison measured Whisper at 20.84% word error rate on Polish medical conversation, a deliberately hard domain with specialist vocabulary and overlapping speakers. That is roughly four times the benchmark, on the same language and the same model family.
Accuracy tracks model size far more than it tracks local versus cloud - it is the same open-source Whisper either way. The compact models are not enough for real Polish dictation; quality becomes usable at the small model and best at the largest. SnailText's free tier covers the compact models, and the larger ones are on Pro.
What makes Polish genuinely hard for speech models
Seven cases, and a long tail of word forms. Polish inflects nouns, adjectives and numerals heavily, so a single dictionary word appears in the wild as dozens of surface forms. Research on Polish ASR benchmarking names this directly: complex morphology drives a high out-of-vocabulary rate, because no training set can contain every form of every word. The practical shape of the error is that the stem is recognised and the ending is not - and in Polish the ending is what carries the case, the number and often the meaning.
Three sibilant series that differ very little acoustically. Polish contrasts s/z, s-acute/z-acute and sz/z-dot, plus the matching affricates c, c-acute and cz. Polish speech-assessment research probes exactly these contrasts as the difficult set, using test words like szafa, szufelka, czapka and dziadek. That work is about screening children's pronunciation rather than about Whisper, so treat it as evidence that these are the hard contrasts in Polish phonology, not as a measurement of what our model gets wrong.
Whisper invents text when it hears no speech, and this was studied on Polish. A 2025 paper investigated Whisper hallucinations induced by non-speech audio and found the model emits fabricated transcript text when fed silence or noise. This is the one challenge on this page where SnailText has a real answer that is not a tuning claim: silence filtering, voice-coverage filtering and a hallucination blocklist run on every transcript. None of that is Polish-specific - it is global and language-agnostic - but the failure it prevents was documented on Polish audio.
What we actually offer for Polish, and what we do not
For Spanish, German, French, Portuguese and Dutch, SnailText ships a language-specific prompt that biases the model toward that language's spelling and punctuation. For Polish we do not. There is no Polish tuning layer, no Polish cleanup pass and no Polish fine-tune, so this page makes no accuracy claim beyond what the open model does on its own. In particular we do not claim to fix dropped diacritics, and we do not claim to resolve the o-acute versus u or z-dot versus rz spellings, which are homophones in modern Polish and can only be inferred from vocabulary.
What SnailText does give you is the best open Polish speech model running entirely on your own hardware, wired into a global hotkey that pastes text at your cursor in any app - email, docs, Slack, your editor. No Python to set up, no model plumbing, no account needed to start.
The hallucination guard is worth one more line because it is genuinely ours and genuinely useful. Whisper's habit of filling silence with invented sentences is well documented, and SnailText filters it at three levels before the text ever reaches your cursor. That protection applies to every language, Polish included.
One practical tip: set the dictation language to Polish explicitly rather than leaving it on automatic. Whisper decides the language from roughly the first thirty seconds and does not revisit that decision, so an English word at the start can colour everything after it.