ASR + NLU pipeline

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.

Clone the SIC repo
1. git clone https://github.com/Social-AI-VU/social-interaction-cloud.git
Switch to the nlu_component branch:
1. git checkout nlu_component
Create and activate a virtual environment:
1. If you are using pure Python environment
```
python -m venv venv_sic
source venv_sic/bin/activate
```
2. If you are using Anaconda environment
```
conda create -n venv_sic python=3.12
conda activate venv_sic
```

Install SIC, nlu and whisper dependencies from local repo:

cd social-interaction-cloud
pip install ."[whisper-speech-to-text,nlu]"

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 ):
```
# Start the Redis server
redis-server conf/redis/redis.conf

# Start the NLU and Whisper components separately
run-whisper
run-nlu
```
Open a new terminal and activate the same virtual environment you created earlier
Clone the sic_applications repo
1. git clone https://github.com/Social-AI-VU/sic_applications.git
Add (trained) nlu model and ontology to the configuration folder sic_applications/conf/nlu. The default names are “model_checkpoint.pt" and "ontology.json".

Run the demo

cd sic_applications/demos/desktop
python demo_desktop_asr_nlu.py