voicelistener

Real-time voice recognition using Whisper or ElevenLabs. Speech detection uses fast RMS energy gating by default; Silero VAD is available as an optional higher-accuracy mode.

Structure

voicelistener/
├── __init__.py
├── __main__.py              # CLI entry point
├── voicelistener.py         # VoiceListener class (audio + VAD + threading)
├── requirements.txt
└── transcribers/
    ├── __init__.py
    ├── whispertranscriber.py      # WhisperTranscriber class
    └── elevenlabstranscriber.py   # ElevenLabsTranscriber class

Installation

pip install voicelistener

CLI usage

# Default (local Whisper)
python -m voicelistener

# ElevenLabs (requires ELEVENLABS_API_KEY env var)
python -m voicelistener --transcriber elevenlabs

Listens to your microphone, detects speech, and prints transcriptions to stdout. Press Ctrl+C to stop.

Library usage

from voicelistener import VoiceListener, WhisperTranscriber, ElevenLabsTranscriber

# Local Whisper
transcriber = WhisperTranscriber(model_id="base.en")

# Or ElevenLabs (set ELEVENLABS_API_KEY env var)
# transcriber = ElevenLabsTranscriber(model_id="scribe_v2")

listener = VoiceListener(transcriber=transcriber)

for text in listener:
    print(text)

Callback style

def handle(text):
    print(f"Heard: {text}")

listener = VoiceListener(
    transcriber=WhisperTranscriber(),
    on_transcription=handle,
)
listener.start()

VoiceListener options

Custom transcriber

Implement a class with a transcribe method:

class MyTranscriber:
    def transcribe(self, audio):
        # audio is a float32 numpy array at 16kHz
        return "transcribed text"

listener = VoiceListener(transcriber=MyTranscriber())