Demonstrating live transcription using a local microphone

The live demo client is found in the inference/live_demo_client directory.

This script connects to a running CAIMAN-ASR server and streams audio from your microphone to the server for low-latency transcription.

Step 1: Set up the CAIMAN-ASR server

Follow the instructions provided in Inference Flow to set up the ASR server.

Step 2: Set up the client

Locally, install dependencies:

sudo apt install portaudio19-dev python3-dev # dependencies of PyAudio
pip install pyaudio websocket-client

(Or if you are a Nix user, nix develop will install those)

Then run the client with ./live_client.py --host <host> --port <port> where <host> and <port> are the host and port of the ASR server respectively.

Prefix (punctuation/casing)

Use --prefix to condition the RNN-T prediction network:

  • <pnc>: punctuated and cased output
  • <nopnc>: lowercase only (slightly more accurate)

For example,

python ./live_client.py --host <host> --port <port> --prefix="<pnc>"

Note: ensure the server is running a model that supports prefix.

Keyword Boosting

CAIMAN-ASR supports keyword boosting of up to 100 keywords. Keyword boosting is a technique to improve the recognition of domain-specific words/phrases and proper nouns, by boosting the probability of specific tokens at inference time.

To provide keywords to the server, use the --keywords argument with a space-separated list of keywords e.g.

python ./live_client.py --keywords caiman asr myrtle

Troubleshooting

If the client raises OSError: [Errno -9997] Invalid sample rate, you may need to use a different audio input device:

  1. Run ./print_input_devices.py to list available input devices
  2. Try each device using (for example) ./live_client.py --input_device 5