About Mix.nlu
Mix.nlu provides a convenient web front-end allowing you to:
- Design an ontology for a domain consisting of intents and entities and their relationships
- Build a training set of samples annotated according to this ontology
- Train and perform basic testing of language models based on the ontology and samples
The end goal of this is to create and refine training sets that can be built into NLU models for Natural Language Understanding (NLU) and domain language models (DLMs) for Automated Speech Recognition (ASR). Model resources are built and deployed from the Mix Project Dashboard.
Client applications can then harness these models to transcribe speech into text using the ASR as a Service gRPC API and interpret text meaning using the NLU as a Service gRPC API.
The underlying ontology developed in Mix.nlu is also shared with the Mix.dialog tool. Mix.dialog is used to design conversational agent models that can leverage ASR and NLU resources to interpret user intent and respond appropriately to what people write and say. Client applications harness dialog models using the Dialog as a Service gRPC API.
Mix.nlu is the departure point for this conversational AI journey.
Note that Mix.api provides a REST API that lets you programmatically interact with your Mix models to perform different tasks, including authoring.More Info:
-
Looking for an introduction to NLU? For an overview of natural language understanding, including the role that intents and entities play in developing an application ontology, see Fundamentals.
-
Looking for best practices of NLU modeling? For guidance on best practices of NLU modeling, see NLU modeling best practices.
-
Looking for best practices of Domain language modeling? For guidance on best practices for building and leveraging DLMs and other speech resources, see ASR models and resources best practices.
Feedback
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.