hub-audio

name	hub-audio
description	Use for audio processing nodes in dora. Triggers on: dora-microphone, dora-vad, dora-distil-whisper, dora-pyaudio, dora-kokoro-tts, microphone, VAD, voice activity, speech-to-text, STT, text-to-speech, TTS, whisper, kokoro, audio, speaker, silero, speech recognition, 麦克风, 语音识别, 语音合成, 音频, VAD
globs	["**/dataflow.yml","**/dataflow.yaml"]
source	https://github.com/dora-rs/dora-hub

Audio Processing Nodes

Microphone input, voice activity detection, speech-to-text, and text-to-speech

Audio Pipeline Overview

Microphone → VAD → Whisper STT → LLM → Kokoro TTS → Speaker

Available Audio Nodes

Node	Install	Description
dora-microphone	pip install dora-microphone	Microphone input with VAD
dora-vad	pip install dora-vad	Silero voice activity detection
dora-distil-whisper	pip install dora-distil-whisper	Distil-Whisper STT
dora-kokoro-tts	pip install dora-kokoro-tts	Kokoro text-to-speech
dora-pyaudio	pip install dora-pyaudio	Audio playback

dora-microphone

Capture audio from microphone with built-in voice activity detection.

YAML Configuration

- id: microphone
  build: pip install dora-microphone
  path: dora-microphone
  inputs:
    tick: dora/timer/millis/100
  outputs:
    - audio  # 16kHz Float32Array

Output Format

# audio: Float32Array at 16kHz sample rate
metadata = {"sample_rate": 16000}

dora-vad

Silero Voice Activity Detection - filters audio to speech-only segments.

YAML Configuration

- id: vad
  build: pip install dora-vad
  path: dora-vad
  inputs:
    audio: microphone/audio  # 8kHz or 16kHz
  outputs:
    - audio  # truncated to speech only

Features

• Detects beginning and ending of voice activity
• Filters out silence and background noise
• Maximum voice duration limit to avoid long waits
• Uses Silero VAD model

dora-distil-whisper

Speech-to-text using Distil-Whisper for efficient transcription.

YAML Configuration

- id: whisper
  build: pip install dora-distil-whisper
  path: dora-distil-whisper
  inputs:
    input: vad/audio
  outputs:
    - text  # StringArray
  env:
    TARGET_LANGUAGE: english  # or other supported languages

Output Format

# text: StringArray containing transcribed text
text = event["value"][0].as_py()  # Get string

dora-kokoro-tts

Efficient text-to-speech using Kokoro.

YAML Configuration

- id: tts
  build: pip install dora-kokoro-tts
  path: dora-kokoro-tts
  inputs:
    text: llm/text
  outputs:
    - audio  # Float32Array

dora-pyaudio

Audio playback through speakers.

YAML Configuration

- id: speaker
  build: pip install dora-pyaudio
  path: dora-pyaudio
  inputs:
    audio: tts/audio

Prerequisites

macOS:

brew install portaudio

Linux:

sudo apt-get install portaudio19-dev python-all-dev

Complete Speech-to-Text Pipeline

nodes:
  # Microphone input
  - id: microphone
    build: pip install dora-microphone
    path: dora-microphone
    inputs:
      tick: dora/timer/millis/100
    outputs:
      - audio

  # Voice activity detection
  - id: vad
    build: pip install dora-vad
    path: dora-vad
    inputs:
      audio: microphone/audio
    outputs:
      - audio

  # Speech to text
  - id: whisper
    build: pip install dora-distil-whisper
    path: dora-distil-whisper
    inputs:
      input: vad/audio
    outputs:
      - text
    env:
      TARGET_LANGUAGE: english

  # Visualization
  - id: rerun
    build: pip install dora-rerun
    path: dora-rerun
    inputs:
      transcription:
        source: whisper/text
        metadata:
          primitive: "text"

Speech-to-Speech Pipeline (Voice Assistant)

nodes:
  # Audio input
  - id: microphone
    build: pip install dora-microphone
    path: dora-microphone
    inputs:
      tick: dora/timer/millis/100
    outputs:
      - audio

  # VAD filtering
  - id: vad
    build: pip install dora-vad
    path: dora-vad
    inputs:
      audio: microphone/audio
    outputs:
      - audio

  # Speech to text
  - id: whisper
    build: pip install dora-distil-whisper
    path: dora-distil-whisper
    inputs:
      input: vad/audio
    outputs:
      - text

  # LLM processing
  - id: llm
    build: pip install dora-qwen
    path: dora-qwen
    inputs:
      text: whisper/text
    outputs:
      - text

  # Text to speech
  - id: tts
    build: pip install dora-kokoro-tts
    path: dora-kokoro-tts
    inputs:
      text: llm/text
    outputs:
      - audio

  # Audio output
  - id: speaker
    build: pip install dora-pyaudio
    path: dora-pyaudio
    inputs:
      audio: tts/audio

Audio Data Format

Float32 Audio Array

import pyarrow as pa
import numpy as np

# Audio at 16kHz
sample_rate = 16000
audio_samples = np.array([...], dtype=np.float32)

# Send audio
audio_data = pa.array(audio_samples)
node.send_output("audio", audio_data, {"sample_rate": sample_rate})

Receiving Audio

audio = event["value"].to_numpy()
sample_rate = event["metadata"].get("sample_rate", 16000)

Troubleshooting

No audio input

# List audio devices
python -c "import sounddevice; print(sounddevice.query_devices())"

PortAudio error

# macOS
brew install portaudio

# Linux
sudo apt-get install portaudio19-dev

Whisper slow on CPU

• Use smaller model (tiny, base)
• Consider dora-funasr for Chinese speech recognition

Related Skills

• hub-llm - Language models for voice assistants
• hub-visualization - Rerun text visualization
• domain-audio - Audio pipeline patterns