Hi Bruno Vaz,
Greetings & Welcome to the Microsoft Q&A forum! Thank you for sharing your query.
Training a Custom Model from a Custom Model:
Unfortunately, Azure Speech Studio does not currently support using an existing custom model as a baseline for further training directly through the UI. This means you can't select your previously trained custom model as the baseline for new training sessions.
Using the REST API:
The REST API for Azure Speech Service might offer more flexibility. You can upload datasets and specify how they are used (for training or testing) when you train a model or run a test. However, the API also follows the same general principles as the UI, so you might still face similar limitations regarding baseline models.
Combining Datasets for Training:
You can train a baseline model with multiple datasets. For your use case, you can use the original audio + human-labeled transcripts dataset along with a custom display text formatting dataset for profanity filtering. This approach should help improve the model's ability to filter out profanity.
Steps to Train with Multiple Datasets:
Upload Datasets: Ensure both datasets (original audio + transcripts and custom display text formatting) are uploaded to your Speech Studio project.
Train a New Model: Select the most recent base model available as your starting point. On the "Choose data" page, select both datasets for training.
Configure Profanity Filtering: Make sure your custom display text formatting dataset includes the necessary rules for profanity filtering.
Additional Resources:
You might find it helpful to refer to the Azure AI services documentation for detailed steps on training custom models and managing datasets
I hope this information helps. Thank you!