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Riva Speech Skills Tutorials

The best way to get started with Riva is to start with the tutorials.

Tutorials

Domain Tutorial Key Words Github URL
ASR How to use Riva ASR APIs with Out-Of-The-Box Models ASR, API Basics Riva ASR - API Basics
ASR How to Customize Riva ASR Vocabulary and Pronunciation with Lexicon Mapping ASR, Customization, Custom Vocab, Lexicon Mapping Riva ASR - Customization - Vocab and Lexicon Mapping
ASR How To Train, Evaluate, and Fine-Tune an n-gram Language Model ASR, Customization, Fine-tuning, Interpolation, n-gram Riva ASR - Customization - Training, Fine-tuning and Deploying n-gram Language Model in NeMo
ASR How to Deploy a Custom Language Model (n-gram) Trained with NVIDIA NeMo on Riva ASR, Customization, Custom Language Model Deployment, n-gram Riva ASR - Customization - Custom Language Model (n-gram) Deployment on Riva
ASR How to Deploy a Custom Acoustic Model (Citrinet) Trained with NVIDIA NeMo on Riva ASR, Customization, Acoustic Model Deployment, Citrinet Riva ASR - Customization - Acoustic Model (Citrinet) Deployment on Riva
ASR How to Deploy a custom Acoustic Model (Conformer-CTC) Trained with NVIDIA NeMo on Riva ASR, Customization, Acoustic Model Deployment, Conformer-CTC Riva ASR - Customization - Acoustic Model (Conformer-CTC) Deployment on Riva
ASR How to Deploy a custom Acoustic Model (Conformer-CTC) Trained with NVIDIA NeMo on Riva with WFST Decoder ASR, Customization, Acoustic Model Deployment, Conformer-CT, WFST Decoder Riva ASR - Customization - Deploy Acoustic Model (Conformer-CTC) with WFST Decoder on Riva
ASR How to Customize a Riva ASR Acoustic Model (Conformer-CTC) with Adapters using NVIDIA NeMo ASR, Customization, Acoustic Model Fine-Tuning, Adapters, NVIDIA NeMo Riva ASR - Customization - Adapters - Acoustic Model Fine-Tuning with NVIDIA NeMo
ASR How to Fine-Tune a Riva ASR Acoustic Model (Conformer-CTC) with NVIDIA NeMo ASR, Customization, Acoustic Model Fine-Tuning, NVIDIA NeMo Riva ASR - Customization - Acoustic Model Fine-Tuning with NVIDIA NeMo
ASR How to Improve Recognition of Specific Words ASR, Customization Riva ASR - Customization Overview
ASR How to Improve Recognition of Specific Grammars and/or Words/Word Sequences (classes) using WFST ASR, Customization, WFST, Class LM, Word Classes Riva ASR - Customization Overview
ASR How to Improve the Accuracy on Noisy Speech by Fine-Tuning the Acoustic Model (Conformer-CTC) in the Riva ASR Pipeline ASR, Accuracy, Acoustic Model Fine-Tuning Riva ASR - Improve Accuracy - Fine-Tuning the Acoustic Model (Conformer-CTC) in ASR Pipeline
ASR How to Boost Specific Words at Runtime with Word Boosting ASR, Customization, Word Boosting Riva ASR - Customization - Word Boosting
ASR The Making of RIVA German ASR Service ASR, New Language Adaptation, German Riva ASR - German
ASR The Making of RIVA Hindi ASR Service ASR, New Language Adaptation, Hindi Riva ASR - Hindi
ASR The Making of RIVA Mandarin ASR Service ASR, New Language Adaptation, Mandarin Riva ASR - Mandarin
Deploy How to Deploy Riva at Scale on AWS with EKS Deploy, AWS EKS Riva - Deploy - AWS EKS
TTS How to use Riva TTS APIs with Out-Of-The-Box Models TTS, API Basics, Customization, SSML, Pitch, Rate, Pronunciation, Emphasis, Sub Riva TTS - API Basics and Customization with SSML
TTS TTS Deploy TTS, Deployment Riva TTS - Deployment on TTS
TTS Evaluate a TTS Pipeline TTS, Evaluate Pipeline Riva TTS - Evaluate a TTS Pipeline
TTS TTS Fine-Tune using NeMo TTS, Fine-Tuning, NVIDIA NeMo Riva TTS - Fine-Tuning using NeMo
TTS Calculate and Plot the Distribution of Phonemes in a TTS Dataset TTS, Phonemes Riva TTS - Phonemes in a TTS Dataset
NMT How to Perform Language Translation using Riva NMT APIs with Out-Of-The-Box Models NMT, API Basics, Translation Riva NMT - API Basics
NMT NMT Fine-Tune using NeMo NMT, Fine-Tuning, NVIDIA NeMo Riva NMT - Fine-Tuning using NeMo
NMT How to Deploy a NeMo Fine-Tuned NMT model on Riva NMT, Customization, Translation model Deployment Riva NMT - Customization - Translation Model Deployment on Riva

Requirements and Setup

Running the NVIDIA Riva Tutorials

This section covers the requirements and setup needed to run all Riva tutorials.

Requirements

Before you try running the NVIDIA Riva tutorials, ensure you meet the following requirements:

Setup

  1. Clone the NVIDIA Riva tutorials repository. git clone https://github.com/nvidia-riva/tutorials.git cd tutorials

  2. Create a Python virtual environment. We will use this virtual environment to install all the dependencies needed for the Riva tutorials. python3 -m venv venv-riva-tutorials

  3. Activate the Python virtual environment we just created. . venv-riva-tutorials/bin/activate

  4. Install Jupyter notebook. pip3 install jupyter

  5. Create an IPython kernel. The Riva tutorials Jupyter notebooks will use this kernel in the next step. ipython kernel install --user --name=venv-riva-tutorials

  6. Start the Jupyter notebooks server. jupyter notebook --allow-root --port 8888

If you have a browser installed on your machine, the notebook should automatically open. If you do not have a browser, copy/paste the URL from the command. Once you open a Riva tutorial notebook on a browser, choose the venv-riva-tutorials kernel by Kernel -> Change kernel -> venv-riva-tutorials.

Running the Riva Client

Requirements

Before you try running the Riva client, ensure you meet the following requirements:

Setup

  1. [Optional] If using the venv-riva-tutorials (or another) Python virtual environment, activate it. . <Python virtual environment directory location>/venv-riva-tutorials/bin/activate

  2. Install nvidia-riva-client using pip.

pip install nvidia-riva-client

Alternatively, you can install it from the source; nvidia-riva/python-clients.

Copyright and License

Copyright 2023 NVIDIA Corporation. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.