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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5 Communication and working together

Chapter 5 Overview: In this chapter, we share some useful tips on effective communication and good working relationships with communities and partners. We show how they can make your language technology projects more successful. These tips are based on our own experience.

The chapter also suggests that you share best practices and lessons learned. We advise you to be fully transparent in the partnership so you can make improvements at any stage.

In summary, this chapter focuses on the different types of communication needed for successful language technology projects. We outline strategies for effective communication within language communities. We also show you how to build strong working partnerships. The focus is on transparency, trust, and learning together.

Use Table 3 from this partner playbook to get a summary of the sections in Chapter 5.

Section

Content

5.1 – Communicating with communities

To develop language technology solutions, you often need a very large amount of language data. In this chapter, we explain the importance of working closely with language communities to create this data. Strategies used may include hiring translators, paying local people for shorter translations, and asking for volunteers to do translations. It is very important that you are clear in your communications about translation. You need to recognize that it is a nuanced process that requires an understanding of the local culture.

To communicate well, you will need to:

  • be clear about your expectations

  • give translators detailed instructions

  • ensure open dialogue to sort out any issues and

make it possible for translators to work together.

5.2 – Communicating and working well with partners

This part looks at the special approach to communication that you need when working with partners. The focus is on long-term thinking and the importance of having clear roles and responsibilities so the partnership will last. We talk about building trust, a gradual process in which each partner has their own unique strengths.

Effective communication means being clear about the expertise that each partner can offer and creating multi-level communication channels. We underline the need for varied channels based on type of information, urgency, and privacy needs. You can make it easier to interact with the user organization through local partner ownership and multichannel engagement. This ensures a user-centered approach.

Table 3: Section summary for Chapter 5

5.2 Communication and Collaboration with Partners:

This part delves into the distinctive communication approach needed when collaborating with partners. It stresses long-term thinking, emphasizing defining roles and responsibilities for enduring partnerships. Building trust is highlighted as a gradual process acknowledging the unique strengths of each partner. Effective communication involves clearly articulating expertise contributions and establishing multi-level communication channels. It underlines the need for varied channels based on information types, urgency, and privacy considerations. User-organization interaction is facilitated through local partner ownership and multichannel engagement, ensuring a user-centered approach. The chapter advocates for sharing best practices, and lessons learned, and maintaining transparency throughout the partnership to foster an environment of continuous improvement.

In summary, this chapter emphasizes the nuanced communication required for successful language technology projects. It outlines strategies for effective communication within language communities and offers insights into building strong, collaborative partnerships with a focus on transparency, trust, and mutual learning.

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.

In this section, we are sharing useful tips gathered from experience on how effective communication and collaboration with communities and partners contribute to successful language technology projects.

Previous4.3 Evaluating What Can Be Done and What WorksNext5.1 Communicating with Communities

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