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:

• Python 3

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:

• You have access and are logged into NVIDIA NGC. For step-by-step instructions, refer to the NGC Getting Started Guide.
• Python 3

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.