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tools.stt: init real-time speech-to-text using vosk
- Add vosk package (offline speech recognition based on Kaldi)
- Streaming STT that reads WAV audio from stdin
- Outputs text as sentences are recognized
- -w flag shows live words on stderr with corrections
- Supports multiple languages (en, de, fr, es, ru, cn, ja)
author
lassulus
date
(Jan 11, 2026, 10:48 PM CET)
commit
b9ac52ca
b9ac52ca6426216b18d4b75fd9143dab6bdbc51e
parent
159bc3a7
159bc3a79d445121da3f6aad171e423cf1fc83dd
+291
+62
5pkgs/vosk/package.nix
+62
5pkgs/vosk/package.nix
···
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{
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lib,
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python3Packages,
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fetchurl,
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stdenv,
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}:
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let
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version = "0.3.44";
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# Platform-specific wheels
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wheels = {
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"x86_64-linux" = {
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url = "https://files.pythonhosted.org/packages/py3/v/vosk/vosk-${version}-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl";
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hash = "sha256-JlLvITxMeAfcQK8eeqV43Mz8TcQZKCKia8RalZG8v3Y=";
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};
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"aarch64-linux" = {
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url = "https://files.pythonhosted.org/packages/py3/v/vosk/vosk-${version}-py3-none-manylinux2014_aarch64.whl";
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hash = "sha256-mZW3+lQ0sTS0vQmJfiSQ28VhFcKtKUPAMGIeEMcDezQ=";
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};
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"x86_64-darwin" = {
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url = "https://files.pythonhosted.org/packages/py3/v/vosk/vosk-${version}-py3-none-macosx_10_6_universal2.whl";
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hash = "sha256-Ap0LPWpc/4dMV1uKWBSkzM+zdgjP9S6EbAKoxnqIKAE=";
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};
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"aarch64-darwin" = {
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url = "https://files.pythonhosted.org/packages/py3/v/vosk/vosk-${version}-py3-none-macosx_10_6_universal2.whl";
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hash = "sha256-Ap0LPWpc/4dMV1uKWBSkzM+zdgjP9S6EbAKoxnqIKAE=";
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};
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};
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wheel =
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wheels.${stdenv.hostPlatform.system}
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or (throw "Unsupported platform: ${stdenv.hostPlatform.system}");
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in
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python3Packages.buildPythonPackage {
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pname = "vosk";
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inherit version;
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format = "wheel";
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src = fetchurl {
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inherit (wheel) url hash;
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};
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dependencies = with python3Packages; [
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cffi
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requests
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tqdm
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srt
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websockets
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];
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# Skip tests as they require audio files and models
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doCheck = false;
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pythonImportsCheck = [ "vosk" ];
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meta = {
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description = "Offline speech recognition API based on Kaldi and Vosk";
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homepage = "https://alphacephei.com/vosk/";
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license = lib.licenses.asl20;
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platforms = lib.attrNames wheels;
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};
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}
+29
tools/stt/flake-module.nix
+29
tools/stt/flake-module.nix
···
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{ ... }:
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{
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perSystem =
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{ pkgs, self', ... }:
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let
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python = pkgs.python3.withPackages (_ps: [
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self'.packages.vosk
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]);
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in
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{
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packages.stt = pkgs.stdenv.mkDerivation {
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pname = "stt";
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version = "0.4.0";
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src = ./.;
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nativeBuildInputs = [ pkgs.makeWrapper ];
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installPhase = ''
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runHook preInstall
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mkdir -p $out/bin
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cp stt.py $out/bin/stt
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chmod +x $out/bin/stt
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wrapProgram $out/bin/stt \
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--prefix PATH : ${python}/bin \
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--set PYTHONPATH ${python}/${python.sitePackages}
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runHook postInstall
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'';
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meta.mainProgram = "stt";
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};
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};
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}
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tools/stt/stt.py
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tools/stt/stt.py
···
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#!/usr/bin/env python3
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"""
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Real-time streaming speech-to-text using Vosk.
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Reads audio from stdin and outputs words as they're recognized.
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"""
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import argparse
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import json
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import os
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import struct
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import sys
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import zipfile
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from pathlib import Path
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from urllib.request import urlretrieve
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from vosk import KaldiRecognizer, Model, SetLogLevel
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MODEL_DIR = Path(os.environ.get("XDG_DATA_HOME", Path.home() / ".local/share")) / "vosk"
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# Small, fast models for real-time streaming
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MODELS = {
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"en": "vosk-model-small-en-us-0.15",
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"de": "vosk-model-small-de-0.15",
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"fr": "vosk-model-small-fr-0.22",
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"es": "vosk-model-small-es-0.42",
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"ru": "vosk-model-small-ru-0.22",
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"cn": "vosk-model-small-cn-0.22",
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"ja": "vosk-model-small-ja-0.22",
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}
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def download_model(lang: str) -> Path:
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"""Download vosk model if not present."""
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model_name = MODELS.get(lang)
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if not model_name:
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# Fall back to English if language not available
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print(f"No model for '{lang}', using English", file=sys.stderr)
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model_name = MODELS["en"]
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lang = "en"
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model_path = MODEL_DIR / model_name
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if model_path.exists():
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return model_path
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print(f"Downloading model {model_name}...", file=sys.stderr)
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MODEL_DIR.mkdir(parents=True, exist_ok=True)
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url = f"https://alphacephei.com/vosk/models/{model_name}.zip"
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zip_path = MODEL_DIR / f"{model_name}.zip"
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urlretrieve(url, zip_path)
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print("Extracting...", file=sys.stderr)
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with zipfile.ZipFile(zip_path, "r") as z:
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z.extractall(MODEL_DIR)
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zip_path.unlink()
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print("Model ready", file=sys.stderr)
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return model_path
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def parse_wav_header(data: bytes) -> tuple[int, int, int, int]:
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"""Parse WAV header, return (sample_rate, channels, bits_per_sample, data_offset)."""
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if len(data) < 44 or data[:4] != b"RIFF" or data[8:12] != b"WAVE":
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raise ValueError("Invalid WAV header")
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pos = 12
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sample_rate = channels = bits_per_sample = 0
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while pos < len(data) - 8:
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chunk_id = data[pos : pos + 4]
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chunk_size = struct.unpack("<I", data[pos + 4 : pos + 8])[0]
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if chunk_id == b"fmt ":
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channels = struct.unpack("<H", data[pos + 10 : pos + 12])[0]
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sample_rate = struct.unpack("<I", data[pos + 12 : pos + 16])[0]
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bits_per_sample = struct.unpack("<H", data[pos + 22 : pos + 24])[0]
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elif chunk_id == b"data":
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return sample_rate, channels, bits_per_sample, pos + 8
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pos += 8 + chunk_size
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raise ValueError("No data chunk found")
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def convert_audio(data: bytes, in_rate: int, in_channels: int, in_bits: int) -> bytes:
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"""Convert audio to 16kHz mono 16-bit for Vosk."""
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import array
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# Align data to sample boundary
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bytes_per_sample = in_bits // 8
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frame_size = in_channels * bytes_per_sample
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aligned_len = (len(data) // frame_size) * frame_size
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if aligned_len == 0:
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return b""
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data = data[:aligned_len]
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# Convert to samples
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if in_bits == 16:
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samples = array.array("h", data)
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elif in_bits == 8:
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samples = array.array("h", [(s - 128) * 256 for s in data])
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else:
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raise ValueError(f"Unsupported bit depth: {in_bits}")
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# Convert to mono
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if in_channels == 2:
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mono = array.array("h")
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for i in range(0, len(samples) - 1, 2):
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mono.append((samples[i] + samples[i + 1]) // 2)
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samples = mono
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# Resample to 16kHz if needed
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if in_rate != 16000:
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ratio = 16000 / in_rate
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new_len = int(len(samples) * ratio)
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resampled = array.array("h")
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for i in range(new_len):
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src_idx = min(int(i / ratio), len(samples) - 1)
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resampled.append(samples[src_idx])
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samples = resampled
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return samples.tobytes()
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def main():
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parser = argparse.ArgumentParser(description="Real-time STT using Vosk")
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parser.add_argument(
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"-l",
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"--language",
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default=os.environ.get("VOSK_LANG", "en"),
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help="Language: en, de, fr, es, ru, cn, ja (default: en)",
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)
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parser.add_argument(
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"-w",
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"--words",
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action="store_true",
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help="Output individual words as they're recognized",
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)
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args = parser.parse_args()
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# Suppress Vosk logging
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SetLogLevel(-1)
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model_path = download_model(args.language)
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model = Model(str(model_path))
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# Read WAV header
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stdin = sys.stdin.buffer
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header_buf = stdin.read(4096)
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sample_rate, channels, bits, data_offset = parse_wav_header(header_buf)
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print(f"Audio: {sample_rate}Hz, {channels}ch, {bits}bit", file=sys.stderr)
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print("Listening...", file=sys.stderr)
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# Create recognizer for 16kHz audio
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rec = KaldiRecognizer(model, 16000)
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rec.SetWords(True)
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# Process initial audio from header buffer
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initial_audio = header_buf[data_offset:]
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if initial_audio:
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converted = convert_audio(initial_audio, sample_rate, channels, bits)
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rec.AcceptWaveform(converted)
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# Process audio stream
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chunk_size = int(sample_rate * channels * (bits // 8) * 0.1) # 100ms chunks
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while True:
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data = stdin.read(chunk_size)
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if not data:
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break
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converted = convert_audio(data, sample_rate, channels, bits)
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if rec.AcceptWaveform(converted):
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result = json.loads(rec.Result())
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text = result.get("text", "")
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if text:
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if args.words:
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# Show final sentence on stderr with period and newline
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print(f"\r\033[K{text}.", file=sys.stderr, flush=True)
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print(text, flush=True)
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elif args.words:
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partial = json.loads(rec.PartialResult())
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text = partial.get("partial", "")
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if text:
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# Show partial with corrections on stderr
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print(f"\r\033[K{text}", end="", file=sys.stderr, flush=True)
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# Final result
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result = json.loads(rec.FinalResult())
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text = result.get("text", "")
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if text:
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if args.words:
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print(f"\r\033[K{text}.", file=sys.stderr, flush=True)
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print(text, flush=True)
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print("Stream ended", file=sys.stderr)
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if __name__ == "__main__":
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main()