Language AI Playbook
  • 1. Introduction
    • 1.1 How to use the partner playbook
    • 1.2 Chapter overviews
    • 1.3 Acknowledgements
  • 2. Overview of Language Technology
    • 2.1 Definition and uses of language technology
    • 2.2 How language technology helps with communication
    • 2.3 Areas where language technology can be used
    • 2.4 Key terminology and concepts
  • 3. Partner Opportunities
    • 3.1 Enabling Organizations with Language Technology
    • 3.2 Bridging the Technical Gap
    • 3.3 Dealing with language technology providers
  • 4. Identifying Impactful Use Cases
    • 4.1 Setting criteria to help choose the use case
    • 4.2 Conducting A Needs Assessment
    • 4.3 Evaluating What Can Be Done and What Works
  • 5 Communication and working together
    • 5.1 Communicating with Communities
    • 5.2 Communicating and working well with partners
  • 6. Language Technology Implementation
    • 6.1 Navigating the Language Technology Landscape
    • 6.2 Creating a Language-Specific Peculiarities (LSP) Document
    • 6.3 Open source data and models
    • 6.4 Assessing data and model maturity
      • 6.4.1 Assessing NLP Data Maturity
      • 6.4.2 Assessing NLP Model Maturity:
    • 6.5 Key Metrics for Evaluating Language Solutions
  • 7 Development and Deployment Guidelines
    • 7.1 Serving models through an API
    • 7.2 Machine translation
      • 7.2.1 Building your own MT models
      • 7.2.2 Deploying your own scalable Machine Translation API
      • 7.2.3 Evaluation and continuous improvement of machine translation
    • 7.3 Chatbots
      • 7.3.1 Overview of chatbot technologies and RASA framework
      • 7.3.2 Building data for a climate change resilience chatbot
      • 7.3.3 How to obtain multilinguality
      • 7.3.4 Components of a chatbot in deployment
      • 7.3.5 Deploying a RASA chatbot
      • 7.3.6 Channel integrations
        • 7.3.6.1 Facebook Messenger
        • 7.3.6.2 WhatsApp
        • 7.3.6.3 Telegram
      • 7.3.7 How to create effective NLU training data
      • 7.3.8 Evaluation and continuous improvement of chatbots
  • 8 Sources and further bibliography
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1. Introduction

Language AI for social impact - a Playbook on how to use language technology for community engagement.

How can CLEAR Global help?

CLEAR Global’s mission is to help people get vital information and be heard, whatever language they speak. We help our partner organizations to listen to the communities they work with and communicate with them effectively. Our tech-focused work helps organizations to find use cases where language technology could help to get users more actively engaged and scale up communications efforts. We develop language AI solutions such as chatbots, machine translation, and speech solutions for low-resource languages. These are languages that don’t have enough data to create such language solutions. CLEAR Global’s user experience (UX) team can help with user research and UX design, and advise on human-centered design to tech interventions. Our Language Services team can translate messages and documents into local languages, help with audio translations and pictures, train staff and volunteers, and advise on two-way communication. We also work with partners to field test and revise materials so they are easier to understand and have more impact. This work is backed up by research and language mapping and by assessing the communication needs of target populations.

For more information visit our website or contact us at info@clearglobal.org.

This playbook is currently still under development by CLEAR Global in collaboration with NLP experts and relevant organizations working to provide feedback and validate the playbook.

Chapter 1 Overview: In this chapter, we introduce CLEAR Global, an organization that aims to make communication across languages more effective. CLEAR Global focuses on developing language AI solutions. These include chatbots, machine translation, and speech solutions. Our main focus is on low-resource languages.

This playbook is a guide for program and technology partners and aims to help them understand and make use of language technology. It looks at various key objectives:

  • learning about language technology

  • understanding relevant terms

  • choosing use cases that will have an impact

  • making communication better and helping people to work together well

  • managing data effectively using language technology

  • making use of chatbots and machine translation.

The playbook focuses on practical application through real-world examples and aims to get partners to learn together. In the “Acknowledgments” section, we thank the various people who have helped with the “4 Billion Conversations” project. We highlight the work of Natural Language Processing (NLP) researchers and partner organizations. Overall, the playbook serves as a helpful and broad resource. It should help people to use language technology to improve communication and get people in their community more actively engaged. Welcome to the Playbook for Language Technology!

This playbook aims to help you understand, develop, and use language technology effectively. You may have little or no knowledge of this technology and maybe just starting to learn about it. Or you may have already used language technology in your work. Whatever the case, this playbook will be your go-to resource. It will help you understand, make use of, and maximize the potential of language technology.

This section of the playbook requires little or no technical expertise and has been designed to be plain and concise with a focus on introducing language technology and how it can be integrated into programs, for organizations looking to use language AI for community engagement.

This playbook is a key resource for program and technology partners. It will help you to understand how to use and develop language technology and give you plenty of practical guidance. The focus is on low-resource and minority languages. The digital world is expanding, and language technology can help bridge gaps in communication and give people better access to information. But the major languages are dominant and this is a problem. We have written this playbook to help organizations build and make use of language technology solutions for low-resource languages. We also want to help organizations find use cases that will have an impact and work with their communities, partners, and supporters to set up successful language technology projects.

Next1.1 How to use the partner playbook

Last updated 1 year ago

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