How accurate is Czech speech to text with local Whisper?
In the Whisper paper itself (arXiv:2212.04356), the large-v2 model scores 13.3% word error rate on Czech FLEURS. It is worth putting that beside its neighbours from the same table and the same model: Dutch 6.7%, German 4.5%. Czech is roughly twice the error rate of Dutch and close to three times German, and a page that implies parity with the big Western European languages would be selling you something.
That figure is clean read speech and acts as a floor. Real dictation in a normal room, in the way people actually speak Czech rather than the way they read it aloud, runs higher - and the gap is larger for Czech than for most languages, for the reasons below.
Accuracy tracks model size far more than it tracks local versus cloud - it is the same open-source Whisper either way. For Czech in particular, use the largest model you can run; the compact free-tier models struggle.
What makes Czech genuinely hard for speech models
Inflection inflates the vocabulary by an order of magnitude. Research on Slavic speech processing puts a number on it: the heavy declension of nouns, pronouns and adjectives together with verb conjugation has a large impact on the size of lexical inventories, and Slavic speech recognition needs a vocabulary ten to twenty times larger than English. For Czech specifically this makes language-model estimates unreliable, which is why researchers turn to morpheme-based models instead of word-based ones.
Spoken Czech is not written Czech. A study of colloquial Czech and speech recognition documents that everyday spoken Czech differs substantially from the formal written standard and produces pronunciation variants absent from standard dictionaries, to the point that systems have to generate and filter pronunciation variants explicitly. The practical consequence for you is direct: the more naturally and casually you speak, the further you are from what the model handles best.
Free word order weakens the safety net. The same body of research names Czech's relatively free word order as a serious complication for automatic speech processing - a subject can appear at the start, the middle or the end of a sentence. Where English models can lean on predictable ordering to recover from an unclear word, Czech offers less of that support. Frequent consonant clusters and fast conversational delivery are also named among the difficulties.
What we actually offer for Czech, and what we do not
For Spanish, German, French, Portuguese and Dutch, SnailText ships a language-specific prompt. For Czech we do not. There is no Czech tuning layer, no Czech cleanup pass and no Czech fine-tune. In particular we do not claim to preserve or restore Czech diacritics - the hacek and acute marks are meaning-bearing, losing one is a real error rather than a cosmetic one, and whether they come out right is down to the model, not to anything we add.
What SnailText does give you is the best open Czech 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.
Given the accuracy above, the honest positioning for Czech is that this is a private, offline way to run the same model everyone else runs, not a claim that Czech recognition is solved. Speaking closer to the written standard and using a larger model are the two things that will actually help.
One practical tip: set the dictation language to Czech explicitly rather than leaving it on automatic. Whisper decides the language from roughly the first thirty seconds and does not revisit that decision.