Speech to Text Conformer Notebook

Speech to Text Conformer Notebook

Logo for Speech to Text Conformer Notebook
End to End workflow for speech to text conformer training with TAO Toolkit and deployment using Riva.
Latest Version
April 4, 2023
Compressed Size
22.32 KB

Automatic Speech Recognition

ASR, or Automatic Speech Recognition, refers to the problem of getting a program to automatically transcribe spoken language (speech-to-text). Our goal is usually to have a model that minimizes the Word Error Rate (WER) metric when transcribing speech input. In other words, given some audio file (e.g. a WAV file) containing speech.

The best place to get started with TAO Toolkit - ASR would be the TAO - ASR jupyter notebooks sample enclosed in this sample. This resource has two notebooks included.

  1. Training: Sample workflow for training an ASR - Conformer model and export the model to a .riva file
  2. Deployment: Sample workflow to consume the .riva file and deploy it to Riva.

If you are a seasoned Conversation AI developer we recommend installing TAO and referring to the TAO documentation for detailed information.


Please make sure to install the following before proceeding further:

  • python 3.6.9
  • docker-ce > 19.03.5
  • docker-API 1.40
  • nvidia-container-toolkit > 1.3.0-1
  • nvidia-container-runtime > 3.4.0-1
  • nvidia-docker2 > 2.5.0-1
  • nvidia-driver >= 455.23

Note: A compatible NVIDIA GPU would be required.


We recommend that you install TAO Toolkit inside a virtual environment. The steps to do the same are as follows

virtualenv -p python3 <name of venv>
source <name of venv>/bin/activate
pip install jupyter notebook # If you need to run the notebooks

TAO Toolkit is a python package that is hosted in PyPI. You may install by using python’s package manager, pip.

pip3 install nvidia-tao

To download the jupyter notebook please:

  1. Download the samples using the ngc cli with the following command
ngc registry resource download-version "nvidia/tao/speechtotext_conformer_notebook:v1.0"
  1. Instantiate the jupyter notebook server
jupyter notebook --ip --allow-root --port 8888


By downloading and using the models and resources packaged with TAO Toolkit Conversational AI, you would be accepting the terms of the Riva license