Text Normalization: Weighted Finite State Transducer

Model Overview

This model is an OpenFST finite state archive (.far) for use within the opensource Sparrowhawk normalization engine [2]. This model has been created for French (fr-FR) text.

Model Architecture

This model uses weighted finite-state transducer (WFST) grammars that map strings in written form to strings in spoken form.

Training

The model was constructed using Nemo toolkit as outlined in Inverse Text Normalization.

How to Use this Model

The Riva Quick Start Guide is recommended as the starting point for trying out Riva models. For more information on using this model with Riva Speech Services, see the Riva User Guide.

Input

This model is part of a pipeline for text to speech and accepts text as input.

Output

The output is normalized text which is then passed to the next stage in the text to speech pipeline.

References

[1] NeMo Inverse Text Normalization: From Development To Production
[2] Google Sparrowhawk

License

By downloading and using the models and resources packaged with Riva Conversational AI, you accept the terms of the Riva license.