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
Powered by GitBook
On this page
  1. 1. Introduction

1.2 Chapter overviews

Previous1.1 How to use the partner playbookNext1.3 Acknowledgements

Last updated 1 year ago

Use Table 1 to guide you through this partner playbook.

Chapter

Content

Chapter 1 – Introduction

We introduce CLEAR Global, and guide you on how to best use this partner playbook.

Chapter 2 – Overview of language technology

We introduce the basic ideas, concepts, and tools used in this field. This chapter also includes a section with a list of the most common terminology so you don’t get lost in jargons and acronyms like NLP, ASR, STT and so on.

Chapter 3 – Opportunities for partners

We look at real-life examples that show how language technology can solve practical problems. The focus here is on reaching marginalized communities using languages that don't have a lot of resources

Chapter 4 – Finding use cases that will have an impact

We explain how to find and understand situations where language technology can make an impact. We'll help you decide if an idea is realistic, and look at the results you can expect.

Chapter 5 –Communication and working together

We look at understanding local community issues, working with partners or local communities to solve problems, and sharing the impact of the projects with these communities. In , we'll also show you ways to collect, organize, and manage the data you need. This is especially relevant for languages that may not have a lot of information available. Good data is very important for language technology to work well.

Chapter 6 – Implementing language technology

This chapter is aimed at a more technical audience to help them design and develop language technology solutions. We present a high-level workflow to navigate the language technology landscape. We show them how to decide whether their language is suitably prepared and evaluate their solution in real life.

Chapter 7 – Guidelines for development and deployment

We present practical knowledge on making use of solutions, with a focus on chatbots and machine translation. This chapter, aimed at a technical audience, dives into building data, training models, deployment, and continuous evaluation for impact.

Table 1: Chapter summary for the partner playbook

Chapter 5