noahs-local-speech-recognition 0.1.4

Easy to use implementation of Vosk local speech recognition

Noah's Local Speech Recognition

This project provides a local, privacy-preserving speech recognition tool using the Vosk speech recognition toolkit and microphone input. It supports keyword detection, timestamped transcription, logging, pause/resume functionality, and model auto-downloading.

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Features

• Offline speech recognition (no internet needed)
• Auto-download of Vosk models if not present
• Realtime transcription with timestamps
• Automatic transcript logging to disk
• Support for pause/resume listening

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Requirements

• Python 3.9+
• vosk
• pyaudio
• tqdm
• requests

Setup:

pip install noahs_local_speech_recognition

On Linux (including Raspberry Pi), pyaudio still depends on system-level PortAudio. Make sure to install portaudio19-dev and pyaudio is working before pip installing noahs_local_speech_recognition which relies on pyaudio to avoid errors.

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Linux Setup Instructions

If you're using Linux, the script attempts to install the required PortAudio libraries automatically. However, you may still need to:

1. Run the script that imports noahs_local_speech_recognition with sudo:

2. Manually install dependencies if issues arise:

   sudo apt-get update
   sudo apt-get install -y portaudio19-dev python3-pyaudio
   pip uninstall pyaudio
   pip install pyaudio
   

These steps ensure that pyaudio is compiled correctly against the system's PortAudio library.

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Demo

To test the speech recognizer locally, simply run this script:

from noahs_local_speech_recognition import get_text_after_keyword, list_microphones, start_speech_listening, stop_speech_listening, get_speech_log, get_speech_log_entry, set_speech_log_response, remove_speech_log_entry, pause_speech_listening, resume_speech_listening

import time

print("Listing available microphone devices:")
list_microphones()

print("\nStarting speech recognition with default input device...")
start_speech_listening(name="robot", stop_talking_delay=2, device_index=None, model_name="vosk-model-small-en-us-0.15")

try:
    while True:
        time.sleep(2)
        print("_________________________")
        entry = get_speech_log_entry()
        if entry and entry["response"] is None:
            heard = entry["content"]
            print(f"I HEARD: {heard}")
            speech_log1 = get_speech_log()
            print(f"SPEECH LOG BEFORE SET RESPONSE: {speech_log1}")
            set_speech_log_response("I have heard what you said")
            speech_log2 = get_speech_log()
            print(f"SPEECH LOG AFTER SET RESPONSE: {speech_log2}")
        if entry and entry["content"] in ["goodbye", "good bye", "bye", "quit", "end", "exit"]:
            break
except KeyboardInterrupt:
    pass
finally:
    stop_speech_listening()

This will:

• Auto-download the Vosk "vosk-model-small-en-us-0.15" model if missing.
• Show available audio devices.
• Look for defualt microphone since device_index=None.
• Begin listening and transcribing speech in real-time based on hearing name="robot" keyword
• Log results with timestamps to a file named like transcript_YYYY-MM-DD_HH-MM-SS.txt.
• Display speech_log before and after having response set in the console.
• Use set_speech_log_response() to flag entries as having been responded to.

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Changing Models

You can modify the model by altering the model_name passed to start_speech_listening():

start_speech_listening(name="robot", stop_talking_delay=2, device_index=None, model_name="vosk-model-small-en-us-0.15")

Other available models:

• vosk-model-small-en-us-0.15
• vosk-model-en-us-0.22
• vosk-model-en-us-0.22-lgraph

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Keyword Mode vs Always Listen Mode

To use Always Listen Mode just use name=None in start_speech_listening():

start_speech_listening(name=None, stop_talking_delay=2, device_index=None, model_name="vosk-model-small-en-us-0.15")

This will transcribe everything, not just things said after the name keyword.

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Known Issues

• Use on debian Linux may require manually setting up pyaudio prior to import
• Automaitic Model download links are hardcoded and limited to 3 options.

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License

MIT License

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Acknowledgements

• Vosk Speech Recognition Toolkit
• TQDM for progress bars