Inverse 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 Spanish (es-US) text.
Model Architecture
This model uses weighted finite-state transducer (WFST) grammars that map strings in spoken form to strings in written 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 speech to text and accepts text as input.
Output
The output is written form text.
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.