Vosk setup — models, small vs full, offline usage & fixes

Don’t want to install Vosk? Drop the file here.

The first 20 minutes of any recording are transcribed free: a recording up to 20 minutes transcribes in full, a longer one is previewed, and a pack from $6 (500 minutes) transcribes the rest and opens every export, and credits never expire.

Set up Vosk offline speech recognition, choose between vosk-model-small and full models, and fix sample-rate errors, empty results and language pack questions.

Setup that works

1

Install

pip install vosk — pure offline, runs on a Raspberry Pi.

2

Model

Download from alphacephei.com/vosk/models — vosk-model-small-* (~50 MB, real-time on anything) or the full models (~1-2 GB, better accuracy).

3

Run

Feed 16 kHz mono PCM chunks to KaldiRecognizer; results stream as JSON.

Fixing the common errors

Recognizer returns empty results

Input MUST be 16 kHz 16-bit mono PCM — feed it anything else and you get silence. Convert with ffmpeg first.

small vs full model?

small = real-time on embedded hardware, noticeably weaker on accents and noise. If you're on a laptop and accuracy matters, Whisper-class models beat both.

Punctuation is missing

Vosk outputs raw lowercase words by design; add the vosk-recasepunc model as a second pass, or use an engine with punctuation built in.

Speaker diarization?

There's a speaker-id model (x-vector) but no turn-taking diarization — pair with an external diarizer or use a hosted pipeline.

More on Vosk: the full Vosk page · Vosk alternatives · all transcription tools

Long recording to get through?

One file up to 10 hours, as an upload or a link: see MP3 to text for long recordings, transcribing a podcast episode and an SRT subtitle file from any recording.

Looking at paid options?

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