Running Kaldi

Before running the container, use the docker pull command to ensure an up-to-date image is installed. This is because nvidia-docker ensures that drivers that match the host are used and configured for the container. Without nvidia-docker, you are likely to get an error when trying to run the container.

  1. Issue the command for the applicable release of the container that you want. The following command assumes you want to pull the latest container.
    docker pull nvcr.io/nvidia/kaldi:19.06-py3
  2. Open a command prompt and paste the pull command. The pulling of the container image begins. Ensure the pull completes successfully before proceeding to the next step.
  3. Run the container image. A typical command to launch the container is:
    nvidia-docker run -it --rm -v local_dir:container_dir 
    nvcr.io/nvidia/kaldi:<xx.xx>-py3

    Where:
    • -it means interactive
    • --rm means delete the container when finished
    • –v means mount directory
    • local_dir is the directory or file from your host system (absolute path) that you want to access from inside your container. For example, the local_dir in the following path is /home/jsmith/data/mnist.
      -v /home/jsmith/data/mnist:/data/mnist

      If you are inside the container, for example, ls /data/mnist, you will see the same files as if you issued the ls /home/jsmith/data/mnist command from outside the container.

    • container_dir is the target directory when you are inside your container. For example, /data/mnist is the target directory in the example:
      -v /home/jsmith/data/mnist:/data/mnist
    • <xx.xx> is the container version. For example, 19.01.
  4. See /workspace/README.md inside the container for information on customizing your Kaldi image.

    For more information about Kaldi, including tutorials, documentation, and examples, see Kaldi Speech Recognition Toolkit.