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This tutorial shows you how to run a simple pipeline (ASR + NLU) where Whisper transcribes your speech and feeds it into the NLU component to run inference

Steps:

Since the NLU component is not yet available on PyPI, for now, we will need to clone the repository and install it locally.

  1. Clone the SIC repo

    1. git clone https://github.com/Social-AI-VU/social-interaction-cloud.git

  2. Switch to the nlu_component branch:

    1. git checkout nlu_component

  3. Create and activate a virtual environment:

    1. python -m venv venv_sic

    2. source venv_sic/bin/activate

  4. Install SIC, nlu and whisper dependencies from local repo:

    1. cd social-interaction-cloud

    2. pip install .[whisper-speech-to-text,nlu]

    3. If you are using zsh, the default shell in macOS, add quotes to escape the brackets:

      1. pip install ."[whisper-speech-to-text,nlu]"

  5. Run the NLU and Whisper components in separate terminals (Don’t forget to run a redis server. See the details here https://socialrobotics.atlassian.net/wiki/spaces/CBSR/pages/2180415493/Getting+started#Step-1%3A-starting-Redis-on-your-laptop ):

    1. run-whisper

    2. run-nlu

  6. Open a new terminal and activate the same virtual environment you created earlier

  7. Clone the sic_applications repo

    1. git clone https://github.com/Social-AI-VU/sic_applications.git

  8. Run the demo (Don’t forget to put your ontology file and an already trained model in conf/nlu folder)

    1. cd sic_applications/demos/desktop

    2. python demo_desktop_asr_nlu.py

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