Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

ITU-T F.746.5 - Framework for a language learning system based on speech and natural language processing (NLP) technology



This Recommendation presents an overview of the framework for a language learning system based on speech and natural language processing (NLP) technology. It describes the features, general requirements and functionality, which is a framework to support language-learning systems. The scope covers a high-level description of architecture, devices, servers and clients. © ITU 2022 All rights reserved

The information about this standard has been compiled by the AI Standards Hub, an initiative dedicated to knowledge sharing, capacity building, research, and international collaboration in the field of AI standards. You can find more information and interactive community features related to this standard by visiting the Hub’s AI standards database here. To access the standard directly, please visit the developing organisation’s website.

About the tool



Tool type(s):




Type of approach:



Usage rights:


Geographical scope:


Tags:

  • System architecture
  • Interoperability

Modify this tool

Use Cases

There is no use cases for this tool yet.

Would you like to submit a use case for this tool?

If you have used this tool, we would love to know more about your experience.

Add use case
catalogue Logos

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.