Translators Without Borders, Author at Translators without Borders Blog

Language and data-driven humanitarian action: 5 takeaways from a recent global discussion

In one word, what comes to mind when you think about language and data collection?

Challenging, expensive, necessary.

These are some of the answers we heard from attendees at a roundtable discussion TWB facilitated during the 2020 GeOnG Forum.

Earlier this month, we were joined by panelists from IMPACT Initiatives, Mercy Corps, and the Internal Displacement Monitoring Centre (IDMC). We spoke about the role of language for data-driven humanitarian action and – crucially – how addressing language barriers can enable affected people to make their voices heard. The panelists shared their experiences and gave examples of why language is relevant at different stages of the data collection process. Here are five main conclusions from the discussion that are relevant for staff of any humanitarian organization that collects data:

1. Consult data on the languages people speak in the targeted area.

Some countries have sufficient data from government censuses to make an informed decision about the relevant language(s) targeted people speak and understand. However, this data isn’t always freely accessible, or easily verifiable. TWB is working with IMPACT Initiatives and other partners to make language data readily available to organizations that listen to and communicate with crisis-affected people. You can also collect this data during your survey to help fill the data gap.

2. Address language bias throughout the data collection process.

Language is usually only taken into account in the preparation phase when survey tools are translated into local language(s). This is often done hastily, without checking the translation quality. Mercy Corps highlighted the need to think carefully about language at each stage, from planning to data analysis and dissemination. This includes translating common questions and answers into as many languages as possible and with appropriate quality assurance procedures as a preparedness measure.

3. Support enumerators as needed and don’t make assumptions about their language skills.

Enumerators often take on many roles: administer a survey, but also act as interpreters, cultural mediators, program specialists and organizational representatives. Language support can take some of the burden off enumerators. Testing their literacy levels and comprehension of key terms can help screen enumerators and identify those that need additional training. Tools like glossaries can help them provide consistent and accurate translations of key terms in local languages and be confident that the person they are interviewing understands them.

TWB research assistants interview Rohingya women in the Cox’s Bazar refugee camps, Bangladesh. Photo by Irene Scott/TWB (2018)

4. Identify ways to deal with unstructured data.

Asking open-ended questions or including “other” as an answer option can allow us to understand a situation in the words of affected people themselves. But this data can be particularly difficult to translate and understand. Regular debriefs with enumerators during data collection can help check the quality of any free text data. Translating open-format answers into a language the data analysis team understands as soon as possible after the data is collected was another lesson highlighted during the session.

5. Use technology solutions appropriate to the context.

This could involve using a simple voice recorder as a quality assurance mechanism for multilingual surveys, as IDMC has piloted in northeast Nigeria. In other contexts, this might mean using Google Translate or other machine translation engines to translate information at speed. But this technology works best for major languages and machine translation needs to be approached with caution about anonymity and privacy. TWB and IMPACT Initiatives are developing machine translation and speech recognition tools adapted to humanitarian contexts and marginalized languages. Watch this space!

Interested to find out more? Check out this infographic with more than 20 language tips for effective humanitarian data collection. Watch the video-recording of the session here. And find information about the other sessions of the GeOnG Forum here.

Written by Mia Marzotto, Senior Communication Officer for TWB

TWB Community Survey Results 2020 are out!

In September 2020 we conducted a survey of our translator community. As a community, you told us that you are keen to work more with us. But you also told us that we need to improve our systems and become better at communicating with you. We’ve heard you, and we’re changing how we do some things.

As you read this blog please check out the interactive data visualizations here. Click the legend to display the survey data by geographic location or as a graph, and use the filter function to correlate age data by employment status or volunteer satisfaction.

As we reviewed the survey results, we were overwhelmed by the passion, drive, and motivations of our diverse community of translators. Thank you for your dedication and skills.

Here is some of what we learned:

Our community is diverse

Half of the respondents are under the age of 34. This suggests that we successfully recruit students and young professionals, but have room to grow with more experienced and retired linguists. While respondents come from 150 countries, the majority reports living either in the US, the UK, or Nigeria. Almost 30% of respondents report being part of a diaspora community which we are keen to involve more in our community efforts in the coming year.

Our community is primarily motivated by helping others

25% of survey respondents indicate that their primary reason for volunteering with TWB is to help others and contribute to a good cause. 20% are motivated by working with a humanitarian organization. 33% of respondents indicate that gaining professional skills and learning new skills are key motivators for them. We are eager to understand in greater detail what skills community members want to acquire so we can offer relevant translation training opportunities in 2021.

Photo from Nigeria country office, July 2018.

Our community is highly satisfied with their experience

72% of volunteers reported that they are “likely” or “extremely likely” to recommend TWB to a colleague. When asked what TWB could do to improve the experience, many requested more communication from TWB, specifically around what we do and the impact of our work. Some also mentioned better tutoring and onboarding of new community members into the system and processes, and instilling a better sense of community. We have taken this feedback on board and we plan to increase our email communication and to add virtual meet-ups to share updates and hear from the community directly.

Our community wants more content to translate

One theme that runs through almost all the comments is that community members want more content to translate. “Find more tasks in my language pair” is the number one request community members have.

2020 has been a challenging year for TWB; we saw spectacular growth not only in the community but also in the content that humanitarian organizations asked us to translate. However, not all language pairs are in equal demand; at times there is a lack of content for language pairs where we have a very active community. Since we want to make sure that all community members get a chance to translate, we will need to find a better balance between the volume of content we offer and the interest of the community. This problem has no easy answer, but will demand some better planning and creativity at our end.

Our community wants a better translation platform and tools

The feedback we received about the TWB translation environment clearly indicates that our platform is outdated and not very user-friendly. For the Kató Platform specifically, the feedback is that “The interface is difficult and confusing to navigate.” For Kató TM, our online CAT tool, the general feedback is that we need to provide more training. “Make things simpler,” “Make things more understandable,” and “Provide training” are frequently repeated comments. We are reviewing our translation environment and will soon introduce changes that should alleviate some of the pain that especially new translators feel. These changes will be gradual but should address some of the feedback we received in the 2020 survey.

We’re looking forward to being even better in 2021

The TWB community more than doubled in 2020. We attribute this growth mainly to the COVID-19 pandemic, which motivated many translators to combat the spread of the virus by translating COVID-related information. With your help we translated more than 5.5 million words of COVID-19 content. This is an outstanding community achievement that has positively impacted the lives of countless people.

But we know we can’t keep doing things the way we always have.

We appreciate the time you took to respond to the survey and are grateful that you are helping us grow as an organization. Together we will give even more information to people in a language that they understand. We look forward to working with you in the new year.

Written by Manuela Noske, Community Manager for TWB.

Conversations avec des chatbots : aider les populations de la RDC à accéder à des informations multilingues sur la COVID-19

Read in English

C’est uniquement en donnant la priorité aux outils de communication bidirectionnels que nous pouvons créer une communication et un accès plus équitables aux informations dont les gens ont besoin pour rester en bonne santé et informés.

« En quoi le coronavirus est-il différent d’Ebola ? »
« Quels sont les symptômes de la COVID-19 ? »
« Combien de fois par jour dois-je me laver les mains ? »
« Comment puis-je me protéger de la COVID-19 ? »

Ce sont des questions que les gens se posent en République démocratique du Congo en lingala, en français et en swahili congolais. Et un robot répond à ces questions, dans leur propre langue. Au fil du temps, le robot apprendra d’autres langues pour permettre à d’autres personnes en RDC de communiquer avec lui.

Le nom du robot est « Uji », qui est l’abréviation de ukingo et jibu, qui signifient respectivement « prévention » et « réponse ». Uji est le premier chatbot multilingue de TWB et joue un rôle clé pour garantir l’accès des gens aux informations de santé qu’ils souhaitent obtenir, dans leur propre langue.

Uji est capable de traiter la communication collaborative et bidirectionnelle

Tout le monde a le droit d’accéder aux informations qu’il souhaite obtenir et dont il a besoin, quand il le veut et dans une langue qu’il comprend. Pourtant, il est fréquent que les informations ne soient disponibles que dans des langues commercialement viables au niveau mondial, ou dans les langues nationales d’un pays. En outre, ces informations ne sont souvent disponibles que de manière descendante car les humanitaires et les organismes de santé décident des informations que les gens peuvent et doivent recevoir.

TWB plaide depuis longtemps pour que les humanitaires et les professionnels du développement intègrent la technologie multilingue dans leurs programmes. Cela permet aux personnes touchées par des crises d’obtenir des réponses à leurs questions de manière proactive et indépendante. Avec les restrictions liées à la pandémie de COVID-19, les personnes touchées par les crises n’ont plus toujours accès aux humanitaires et de nouveaux outils de communication sont nécessaires.

Uji réunit la langue et la technologie pour nous rapprocher de cette vision d’un accès véritablement équitable à l’information.

Le développement de Uji

En RDC, l’accès à des informations crédibles et multilingues sur la COVID-19 est un vrai défi. « Pour de nombreuses personnes parlant le lingala et le swahili congolais en RDC, l’accès aux informations sur la COVID-19 se fait par toute une gamme d’émissions de radio, de sites web et d’affiches », explique Rodrigue Bashizi, responsable de l’engagement communautaire de TWB en RDC. « Mais le principal défi pour accéder à l’information sur la COVID-19 est le coût des forfaits de connexion Internet dans le pays. Parfois, les gens reçoivent des vidéos sur la COVID-19, mais ils ne peuvent pas les ouvrir en raison du manque de services Internet de qualité et du coût des forfaits. »

Il fallait proposer aux gens une meilleure solution pour qu’ils puissent obtenir des réponses à leurs questions sur la COVID-19. Accéder à Uji. Selon Rodrigue, « Uji est un outil très important pour les populations de la RDC car elles manquent d’informations fiables. Comme Uji fonctionne sur Telegram et WhatsApp, il ne consommera pas beaucoup de forfait Internet. Il est facile à utiliser. Lorsqu’il fonctionnera par SMS, il sera même disponible pour les populations des régions éloignées n’ayant pas accès à Internet ».

Rodrigue est originaire de Bukavu en RDC et parle le swahili, le français, l’anglais, le lingala, le kinyarwanda et le luganda. Avant de rejoindre TWB, il a travaillé comme formateur auprès de réfugiés en Ouganda. Au sein de TWB, Rodrigue est un membre clé de l’équipe qui développe nos chatbots multilingues pour les communications bidirectionnelles. Rodrigue est passionné par la technologie et explique qu’il adore travailler sur les chatbots, car il apprend quelque chose de nouveau chaque jour.

Rodrigue et d’autres membres de l’équipe TWB ont développé cet outil en partenariat avec Kinshasa Digital, une agence de communication de la RDC qui travaillait déjà avec le ministère de la santé de la RDC pour développer un chatbot COVID-19. Grâce à la collaboration avec Kinshasa Digital et l’ajout d’une technologie multilingue au bot existant, nous serons en mesure d’atteindre plus de personnes, dans plus de langues.

Nous avons développé Uji en français, en swahili congolais et en lingala. Le bot répond à un large éventail de questions sur la COVID-19, allant des symptômes et de la démystification des rumeurs populaires aux conseils sur la manière d’aider les enfants à faire face au stress dû à la COVID-19. Nous travaillons à l’élargissement de son champ d’application afin de répondre également aux questions concernant Ebola. Le chatbot est disponible sur WhatsApp et Telegram. En utilisant les plate-formes de messagerie existantes, les gens peuvent accéder aux informations sur la COVID-19 où qu’ils soient, quand ils le souhaitent. Qu’ils soient à la maison, dans le bus ou au travail, ils peuvent trouver les informations dont ils ont besoin, directement à partir de leur téléphone.

Uji utilise la technologie de traitement du langage naturel pour permettre aux gens de poser des questions dans leurs propres mots.

Pour dialoguer avec Uji, les utilisateurs envoient leurs questions sur la COVID-19 au chatbot sur WhatsApp ou Telegram. Ils peuvent poser leurs questions en français, en swahili congolais ou en lingala. Le bot répond automatiquement dans la langue dans laquelle la question a été posée.

Mais avant de lancer complètement le bot sur ces plates-formes, nous avons dû le tester et le perfectionner.

Testé et approuvé par des linguistes

Uji est un travail de longue haleine, et il nécessite des tests humains dans de nombreuses langues pour s’assurer de son efficacité et de son utilité. Rodrigue a dirigé les activités de test avec des volontaires de la communauté des traducteurs de TWB, de la FICR et d’autres partenaires. Au début du processus, Uji a dû apprendre à comprendre les questions et à leur associer correctement des réponses. Avec le temps et grâce aux tests successifs, Uji s’est amélioré de façon spectaculaire. Et les réactions de notre communauté de testeurs sont positives :

« Le bot fait de grands progrès en swahili. »
« Il est de plus en plus difficile d’obtenir une réponse qui ne correspond pas à la question. Il semble que le robot s’améliore continuellement. »

Ce retour d’information individuel est important, mais on constate également que près de 70 % des utilisateurs ayant participé à notre enquête de satisfaction sur le bot trouvent les informations fournies par Uji utiles. Le chatbot permet également à TWB de recueillir des informations sur les questions les plus fréquemment posées et les langues les plus utilisées. Les organisations humanitaires et sanitaires peuvent utiliser ces données pour mieux adapter leurs stratégies de communication à ce que veulent réellement les communautés.

Nous continuerons à améliorer Uji dans les semaines et les mois à venir, et nous accueillerons volontiers les commentaires supplémentaires des utilisateurs.

L’avenir des chatbots TWB

Nous espérons qu’Uji est le début d’une restructuration globale de la façon dont les conversations multilingues se déroulent. Notre objectif est de démontrer l’utilité d’Uji en tant qu’exemple réussi de canal de communication bidirectionnel multilingue en RDC, puis d’étendre le modèle à d’autres pays et à d’autres utilisations.

Nous encourageons les professionnels de l’humanitaire et du développement à envisager l’intégration de chatbots et d’autres technologies linguistiques dans leurs programmes.

Pour en savoir plus sur l’intégration des technologies de chatbot et de langage dans vos programmes, contactez-nous par email à corona @translatorswithoutborders.org.

Rédigé par Krissy Welle, responsable de la communication de TWB

Eight plain language tips for writers and translators on International Plain Language Day

Two weeks after International Translators Day it’s time to acknowledge International Plain Language Day. TWB’s plain-language adviser, Kate Murphy sees a definite connection between the two.

Kate Murphy, TWB's Plain Language Editor — Kate Murphy, TWB’s Plain Language Adviser

The theme of International Plain Language Day this year is “Access for all starts with plain language.” But I believe that access for all finishes with plain language too. Plain language is relevant from the writer’s first draft to the translator’s last review.

Plain language principles are relevant to anyone who works with words. That applies whether you write words, speak them, read them, or translate them. It applies especially if you translate words into marginalized languages, because your readers often have no other sources of information.

As a writer or translator in the humanitarian sector, unless you’re advocating for and practicing plain-language writing and plain-language translations, you’re not promoting access for all. The alignment of International Translators Day and International Plain Language Day reminds us that writers and translators have a great opportunity to work together to improve access to information. For sure, a clear source document helps a translator to produce a clear target document. But a translator who doesn’t actively apply plain language principles to their translation can unintentionally undermine the writer’s efforts to be clear. They’ll make it harder for readers to access the information they need. Similarly, a translator that understands plain language can convert a poorly written source document into a version that improves readers’ access to clear and unambiguous information. Close collaboration between authors and translators is an important step in producing clear documents. So for me, it’s entirely fitting that International Translators Day and International Plain Language Day align.

Plain language is about much more than simple words

The Program for the International Assessment of Adult Competencies suggests that 49% of adults in OECD (Organization for Economic Co-operation and Development) countries have low literacy. The literacy levels in non-OECD countries are likely to be lower. Plain language will give those people greater access to information. But the hidden and often unappreciated value of plain language is that it reduces the reading effort for all readers, regardless of their literacy level. Plain language is for anyone who wants clear, concise information.

Whoever you are writing or translating for, plain language is always about more than simple words. A complex range of factors determines literacy levels and reading speed; vocabulary is only one of those factors. Fundamentally plain language is about the consistency and conciseness of your message. It’s also about the way you arrange the components to guide the reader through a logical flow of ideas that’s easy to navigate and understand. It’s about consciously using grammar and sentence structures that require the least effort from the reader.

In celebration of International Translators Day and International Plain Language Day, here are eight plain-language principles that writers and translators can use to give access for all.

Written by Kate Murphy, TWB's Plain Language Adviser.

Community translation supports the COVID-19 response

Translators play a key role in slowing the spread and supporting people through the pandemic. So much so that the theme of International Translation Day, 2020 is “Finding the words for a world in crisis.” COVID-19 has without question put the spotlight on the need for language support during a crisis.

For International Translation Day 2020, we’re celebrating our translator community. Like many organizations, Translators without Borders and the translators who work with us have had to pivot to keep up with rapidly changing expectations. The need to overcome language barriers in providing public health information has never been clearer. Our translators have been at the forefront of providing accurate, clear, and consistent information to people who need it, in a language they understand.

This year, our translators’ contributions are supporting more people than ever through an unprecedented crisis of information.

Our community of 30,000 translators has come together to translate critical public-facing content into languages and formats that more people can understand. Since January, we’ve translated 4.8 million words in 101 languages for the COVID-19 response.

For this very special International Translations Day, we interviewed two translators who are dedicating time to COVID-19 projects.

First and foremost, our community is made up of individuals with immense motivation to do good with their translation skills. Like most of us, they are living through times of intense change and readjustment, while finding time to volunteer. So today, on International Translation Day 2020, learn more about these two translators:

Barbara Pissane, based in Lyon, France

Green-tea drinker and dark-chocolate lover
Proud recipient of two French RPL (Recognition of Prior Learning) diplomas
Interested in international relations, ethics, refugees, human rights, and medical devices

Barbara Pissane standing in a city street.

“I love discovering new subjects and working with people from all around the world.”
Barbara Pissane

Maria Paula Gorgone, an Argentinian living in Norway

Committed translator
Works from home and is adjusting to “the new normal”
Has met some amazing people through TWB who she is now “lucky to call friends”

Maria Paula Gorgone sits on top of a hill after a hike.

“I believe that information is a right and everyone should have access to it. The organizations that we get to support through TWB aid people who are in situations where lack of information or misunderstandings can have serious consequences. No one should be left aside because of a language barrier, and I just hope that by volunteering my skills I can do a small part to help break these barriers.”
Maria Paula Gorgone

Barbara and Maria Paula are long-time supporters of Translators without Borders, and now volunteers to review translation tests for French and Spanish. As well as translating tasks, they help us verify new translators, which directly improves the quality of TWB’s projects. Here are some of their major contributions as TWB translators:

Barbara Pissane: translator

English to French translator, reviser and proofreader
Translation Marathon winner
Won the Access to Knowledge Award for Empowerment in 2018
Revised over 50,000 words for COVID-19 projects, 700,000 words since starting with TWB

Maria Paula Gorgone: translator

English to Spanish translator and reviser
Revised 57,000 words for COVID-19 projects
Translated nearly 500,000 words since starting at TWB

Right now, translation work for COVID-19 is especially relevant, and significant for many. Barbara and Maria Paula have worked on the following projects for various nonprofit partners in the past few months.

Barbara Pissane: COVID-19 contributor

Core Group Consortium: This COVID-19 Library offers health workers and trainers access to quality assured, openly licensed content that can be used on mobile devices and shared amongst communities.

Partners in Health: Translations included work on COVID-19 patient management for medical staff with a focus on health issues for poor and marginalized people. The information included how to initially assess a patient with the coronavirus, oxygen management, management of organ failure, COVID-19 triage and screening. Barbara also revised the “COVID-19 Guide: Clinical Management of COVID-19,” a document used across many countries as a guide for community and clinical management of the disease.

H2H Network: Barbara revised several COVID-19 H2H Network resources for a joint project with TWB, to provide robust evidence on the prevention and treatment of COVID-19.

WHO: Barbara translated an online course for “Emerging respiratory viruses, including nCoV: methods for detection, prevention, response and control,” available on OpenWHO online. You can access the course here.

Maria Paula Gorgone: COVID-19 contributor

ACAPS: Maria Paula revised a task for ACAPS, a nonprofit, independent information provider. The project focused on Mexico: migration and COVID-19, a report that provides an overview how the spread of COVID-19 has led to a deteriorating situation for migrants in Mexico. It primarily focuses on how the pandemic has provided an opportunity for US immigration policy to become even more stringent.

Partners in Health: Maria Paula revised an online resource titled “COVID-19 Disproportionately Impacts Immigrants in Massachusetts.” This story is about the work of the Massachusetts Community Tracing Collaborative (COVID-19 contact tracing initiative) and how contact tracers are working with immigrant communities.

War Child: Maria Paula worked on a subtitling project, Child Safeguarding during the COVID-19 response. She also revised the Child Protection Case Management guide for development or humanitarian settings. It is a way of organizing and carrying out work to address children’s and families’ needs in an appropriate, systematic and timely manner.

MSF (Médecins Sans Frontières or Doctors without Borders): This translated document, on “Emergency and Basic Critical Care for COVID-19 in Resource-Limited Settings” provides clinical guidance for COVID-19 patient care in MSF’s existing field projects in resource-limited settings.

WHO: Maria Paula joined fellow translators to work on an online course on emerging respiratory viruses. The training materials on respiratory diseases and critical care for the WHO stood out as an impactful project for her:

“I remember working on this task very early on the pandemic, at a time where everything was a bit confusing and there was a lot of misinformation going around. It was a great feeling knowing I was doing my small part to fight misinformation.”
Maria Paula Gorgone

Thank you to all of the translators who directly contribute words in this crisis, and the partners and supporters who facilitate this vital work. To join our unique community, click here.

Written by Ambra Sottile, Senior Community Officer, and Danielle Moore, Communications Officer for TWB.

Conversations with chatbots: helping people in the DRC access multilingual COVID-19 information

“How is coronavirus different from Ebola?”

“What are the symptoms of Corona?”

“How many times a day should I wash my hands?”

“How else can I protect myself from Corona?”

These are questions that people are asking in the Democratic Republic of Congo in Lingala, French, and Congolese Swahili. And their questions are being answered by a bot, in their own language.

The bot’s name is “Uji,” which is short for ukingo and jibu, which mean “prevention” and “response” respectively. Uji is TWB’s first multilingual chatbot and a key part of making sure people have the health information they want, in their own language.

Uji supports collaborative and two-way communication

Everyone has the right to access the information they need and want, when they want it, and in a language they understand. Yet frequently information is only available in global commercially-viable languages, or in the national languages of a country. Furthermore, this information is often only available in a top-down manner, with humanitarians and health agencies deciding what information people can and should receive.

TWB has long advocated for humanitarians and development professionals to integrate multilingual technology in their programs. This allows people living through crises to proactively and independently get answers to their questions. And with the COVID-19 pandemic related restrictions denying crisis-affected people access to humanitarians, new communication tools are needed.

Uji unites language and technology to bring us closer to this vision of truly equitable information access.

The development of Uji

Access to credible, multilingual COVID-19 information is a challenge in the DRC. “Many Lingala and Congolese Swahili speakers in the DRC are accessing COVID-19 information from different radio shows, websites, and posters,” explains Rodrigue Bashizi, TWB’s DRC Community Engagement Officer. “But the main challenge for accessing COVID-19 information is the cost of internet bundles in the country. Sometimes people receive videos talking about COVID-19, but they can’t open them due to a lack of good internet and the cost of bundles.”

People needed a better solution for their COVID-19 questions. Enter Uji. Rodrigue says, “Uji is a very important tool for people in DRC because they lack trusted information. Since Uji is on Telegram and WhatsApp, it will not consume a lot of internet bundles. It is easy to use. Once it is on SMS it will even be available for people in remote areas with no internet access.”

Rodrigue is from Bukavu in the DRC and speaks Swahili, French, English, Lingala, Kinyarwanda and Luganda. Before joining TWB, he worked as a trainer with refugees in Uganda. At TWB, he is a core member of the team developing our multilingual chatbots for two-way communications. Rodrigue is passionate about technology and says he loves working on chatbots, as he is learning something new every day.

Rodrigue and other TWB team members developed the tool in partnership with Kinshasa Digital, a DRC communication agency that was already working with the DRC Ministry of Health to develop a COVID-19 chatbot. By collaborating with Kinshasa Digital and bringing multilingual technology to the existing bot, we will be able to reach more people, in more languages.

TWB developed Uji in French, Congolese Swahili, and Lingala. The bot responds to a wide range of questions about COVID-19, from debunking popular rumors, to tips on how to help children cope with stress due to COVID-19. We are working on expanding its scope to also respond to questions about Ebola. The chatbot is available on WhatsApp and Telegram. By using existing messaging platforms people can access COVID-19 information wherever they are, whenever they want. Whether they are at home, on the bus, or at work, they can find the information they need, right from their phone.

To engage with Uji, users message their COVID-19 questions to the chatbot on WhatsApp or Telegram. They can ask their questions in French, Congolese Swahili, or Lingala. The bot automatically responds in the language in which the question was asked.

The questions were ready and the bot was developed. But before launching the bot fully across these platforms, we needed to test and perfect it.

Linguist-tested and approved

Uji is a work in progress, and it requires human testing in multiple languages to make sure it’s effective and useful. Rodrigue led the testing efforts with volunteers from TWB’s community of translators, IFRC, and other partners. At the beginning of the process, Uji had to learn to understand questions and match responses accurately. But with time and testing, Uji has improved dramatically. And feedback from our community of testers is positive:

“The bot is making great progress in Swahili.”

“It’s getting harder to get an answer that doesn’t match the question. Seems the bot is improving continuously.”

Not only is this individual feedback important, but nearly 70% of users who participated in our satisfaction survey about the bot report that they find the information useful. The chatbot also allows TWB to gather insights about what questions are asked most frequently and what languages are used most often. Humanitarian and health organizations can use this data to tailor their communication strategies, to better provide the information that people want.

We will continue to improve Uji in the coming weeks and months, and welcome additional feedback from users.

The future of TWB chatbots

We hope that Uji is the start of a global restructuring of how multilingual conversations happen. Our aim is to demonstrate Uji’s value as a successful multilingual two-way communication channel in the DRC, and then expand the model into additional countries and for additional uses.

We encourage humanitarian and development professionals to consider incorporating chatbots and other language technology into their programming.

To learn more about incorporating chatbot and language technology into your programming, email [email protected].

Written by Krissy Welle, TWB’s Senior Communications Officer

The latest from TWB’s language technology initiative

Leaping over the language barrier with machine translation in Levantine Arabic

When a language you don’t understand appears in your Facebook news feed, you can click a button and translate it. This kind of language technology offers a way of communicating not just with the millions of people who speak your language, but with millions of others who speak something else.

Or at least it almost does.

Like so many other online machine translation systems, it comes with a caveat: it is only available in major languages.

TWB is working to eliminate that rather significant caveat through our language technology initiative, Gamayun. We named it after a mythical birdwoman figure in Slavic folklore — she is a magical creature that imparts words of wisdom on the few who can understand her. We think she’s a perfect advocate for language technology to increase digital equality and improve two-way communication in marginalized languages.

We have reached an important Gamayun milestone by leaping over the language barrier with a machine translation engine in Levantine Arabic. Here is how we got here, what we learned, and what is next.

What is behind developing a machine translation engine in Levantine Arabic?

In November 2019, we joined forces with a group of innovators and language engineers from PNGK and Prompsit to address WFP’s Humanitarian Action Challenge. Our goal was to use machine translation to enhance the way aid organizations understand the needs and concerns of Syrian refugees, to improve food security programming.

So we developed a text-to-text machine translation (MT) engine for Levantine Arabic tailored to the specifics of refugees’ experiences. To achieve this, we collaborated with Mercy Corps’ Khabrona.Info team. The team runs a Facebook page for Syrian Arabic refugees to provide them with reliable information and answers, such as about accessing food and other support. We took content shared on the Khabrona.Info Facebook page and manually translated it into English to adapt the engine. The training data and a demonstration version of our MT are available on our Gamayun portal.

How well does this machine translation engine perform?

To answer this question, we conducted an evaluation based on tests widely used by MT researchers. We found that our MT engine produced better translations for Levantine Arabic than one of the most used online machine translation systems.

We first asked experienced translators to rate the translations for both accuracy and fluency. We provided them with ten randomly selected source texts and translations generated by humans, Google’s MT, and our MT. All translations were fairly good, with scores ranging from zero for no errors to three for critical errors. Our MT engine performed slightly better than Google’s MT because it was adapted to the specifics of Levantine Arabic and its online colloquialisms about food security and other topics relevant to refugees’ experiences. The human translations performed slightly better than our MT, but were not perfect.

We also asked the experienced translators to rank the best, second best, and worst translations based on each source text. While the human translations were consistently ranked higher than both machine translation engines, our MT was preferred 70% of the time over Google’s MT.

We then used the standard metric for automated MT quality testing called BLEU. The bilingual evaluation understudy scores an MT translation according to how well it matches a reference for human translation. Scores range from zero for no match to 1.0 for a perfect match, but few translations score 1.0 because all translators will produce slightly different texts. Our generic MT engine trained on publicly available parallel English-Arabic text obtained a 0.195 score on a testing set of 200 social media posts. With further training with a small but specific set for Levantine Arabic and its online colloquialisms, it reached a 0.248 score. Instead, the Google MT translations scored 0.212 on the same testing set.

Take the short sentence أسعار المواد الغائية مرتفعة as an example: humans translated it as “food is expensive” and our MT returned “food prices are high;” Google’s MT, instead, translated it as “the prices of the materials are high.” All are grammatically correct results, but our MT tended to better pick up the nuances of informal speech than Google’s MT. This may seem trivial, but it is critical if MT is used to quickly understand requests for help as they come up or keep an eye on people’s concerns and complaints to adjust programming.

What makes these results possible?

We specifically designed our MT engine to provide reliable and accurate translations of unstructured data, such as the language used in social media posts. We involved linguists and domain experts in collating and editing the dataset to train the engine. This ensured a focus on both humanitarian domain language and colloquialisms in Levantine Arabic.

The agility of this approach means the engine can be used for various purposes, from conducting needs assessments to analyzing feedback information. The approach also meets the responsible data management requirements of the humanitarian sector.

What have we learned?

We have demonstrated that it is possible to build a translation engine of reasonable quality for a marginalized language like Levantine Arabic and to do so with a relatively small dataset. Our approach entailed engaging with the native language community and focusing on text scraped from social media. This holds great potential for building language technology tools that can spring into action in times of crisis and be adapted to any particular domain.

We also learned that even human translations for Levantine Arabic are not perfect. This shows the importance of building networks of translators for marginalized languages who can help build up and maintain language technology. Where there are not enough—if any—professional translators, a key first step is training bilingual people with the right skills and providing them with guidance on humanitarian response terminology. This type of capacity building can not only make technology work for marginalized language speakers in the longer term, but also ensure they have access to critical information in their languages in the shorter term.

What’s next?

We are refining our approach, augmented by external support, to achieve the full potential of language technology. We are currently working with the Harvard Humanitarian Initiative and IMPACT Initiatives using natural language processing and machine learning to transcribe, translate, and analyze large sets of qualitative responses in multilingual data collection efforts to inform humanitarian decision making. We have also joined the Translation Initiative for COVID-19 (TICO-19), alongside researchers at Carnegie Mellon and major tech companies including Amazon, Facebook, Google, and Microsoft to develop and train state-of-the-art machine translation models in 37 different languages on COVID-19.

Stay tuned to learn how we move forward with these projects. We’ll continue to develop language technology solutions to enhance two-way communication in humanitarian crises and amplify the voices of millions of marginalized language speakers.

Written by Mia Marzotto, Senior Advocacy Officer for Translators without Borders.

COVID-19 rumors highlight the need for facts

Disseminating clear, accurate and accessible information in a language that people understand is critical to tackling misinformation and slowing the spread of COVID-19. The UN Secretary-General António Guterres highlighted that alongside the virus itself the world faces a “dangerous epidemic of misinformation.”

Misinformation fills the spaces left when people’s voices aren’t heard and their questions aren’t answered.

Monitoring social media and other discussion platforms are important ways to understand people’s concerns and identify the false information circulating. Health officials and humanitarian organizations involved in the response need to invest in multilingual fact-checking to ensure people have access to the information they need and want. Translators without Borders has partnered with Internews to monitor social media channels in Simplified Chinese, Vietnamese, Tagalog, Indonesian and Urdu to identify trending misinformation. Here is what we are hearing, how it relates to lessons from past outbreaks, and what responders should do about it.

What are we hearing?

Our monitoring reveals that people are looking for answers and wide-ranging rumors are abundant. Questions such as “Can mosquitoes transmit COVID-19?”, “Can the virus survive in hot weather?”, or “Are people with Type A blood more likely to catch COVID-19?” are common across language groups. Often these questions are left unanswered or answered only with speculation from other social media users.

The most persistent rumors we hear are around ways to avoid catching the virus. Eating garlic, ginger, eggs, pepper or bananas, taking Vitamin D, drinking local herbal infusions, or gargling with salt water are just some of the preventive measures circulating. None of them is true. Trending posts containing inaccurate information about supposed cures often misrepresent it as recommendations from “health experts.” Some incorrect information and advice has been wrongly attributed to organizations like UNICEF.

Some proposed “cures” have negative consequences, like those that encourage excessive alcohol, smoking or taking various medications. In extreme cases, misinformed posts have had life-threatening consequences. Another recurrent dangerous theme is fear of people who have contracted COVID-19. This escalates sometimes to posts inciting violence against sick people to stop the spread.

Our team has heard rumors which link mosquito bites to COVID-19. To date, there has no been evidence to suggest that the virus could be spread by mosquitoes. See the WHO myth-busting page for more information.

Simple and accessible formats work

Our work shows that the rumors that spread quickly are often very simple and use words or images that are easily accessible. Memes and messages including video or audio have greater potential to go viral, whether they contain factual information or not. These formats are easily shareable and digestible by all audiences.

This is a stark reminder that both language and format matter to ensure fact-checked information reaches everyone, including the most vulnerable and non-literate individuals.

Lessons from past outbreaks apply

The problem of misinformation in public health emergencies isn’t new. Lessons from the most recent Ebola outbreak in the Democratic Republic of Congo provide insight into its impact and how to address it. TWB found that people wanted answers to their questions about the disease, not just general instructions. Without up-to-date information in plain and accessible languages and formats, people wondered if they were being told the truth, and rumors persisted. The use of technical terms and concepts that were not consistently or clearly translated and explained in local languages created further confusion, frustration, and fear. Several people told us they did not seek treatment for fear of misunderstanding or being misunderstood – and being misdiagnosed with the disease as a result. Health communicators often lacked detailed knowledge of the latest developments to calm people’s fears and address questions.

This contributed to an environment of distrust between responders and community members. While the Ebola outbreak is not yet over, concerted efforts to address communities’ concerns and counter misinformation in their languages has played a crucial role in controlling it.

Trust in the source is linked to whether a message is believed

Trust in the source is an important determinant of whether a message is believed. When information is delivered by a trusted friend or family member, or via a trusted news source or local authority, it is more likely to be believed. Our recent research in Bangladesh confirms that people often prefer to receive information about COVID-19 from these trusted sources. This lesson should be leveraged in rumor-countering strategies.

What should COVID-19 responders do?

Rumors about COVID-19 are circulating widely, repeated across multiple media and in multiple languages. Ignoring or dismissing them isn’t wise, even if some may seem less influential. These rumors will persist unless people have the information they want. Health officials and organizations involved in the response can ensure people have access to timely and factual information that they can understand. Here are three key actions responders must take:

1. Understand people’s questions and concerns.

That means not just giving them information, but listening to them. Monitor social media and other discussion platforms to understand what information people need and want, especially where expert information on COVID-19 is not available in their languages. Language technology such as natural language processing, machine translation, and automated keyword tracking make this possible at scale, even for marginalized languages.

2. Develop rumor-countering messaging based on people’s questions and concerns.

That messaging should be multilingual, accessible, and actionable. Don’t stick to communication only in the official or dominant languages; instead, translate key messages and materials into the languages people understand. And consider people’s literacy levels and intellectual and physical impairments: audio and audiovisual formats can increase the reach of key messages. Avoid jargon or technical terms that many people won’t understand; instead, use simple words that engage with people’s concerns and don’t stigmatize. Develop messaging that makes the situation feel manageable, with advice that is relevant to people’s specific situations.

For example, WHO is developing pictorial myth-busting postcards, and IFRC publishes a weekly factsheet to dispel popular rumors. Such resources are urgently needed in a wider range of languages and in formats that people can easily share through different channels.

3. Partner with trusted, local influencers.

Community leaders, religious leaders, health workers, and local media outlets can amplify dissemination and engagement efforts. Involving them will increase the uptake of key messages in relevant languages and formats.

Here are some useful resources: Internews: rumor tracking methodology and CDAC: Rumour has it: guidance on working with rumours.

For more information on TWB’s COVID-19 language services, please contact us at [email protected].

Written by Manmeet Kaur, COVID-19 Response Lead, and Mia Marzotto, Senior Advocacy Officer for Translators without Borders

This project is funded by the H2H Fund, a funding mechanism for H2H Network members. The fund is a rapid funding vehicle for network members responding to humanitarian crises.

সাইনবোর্ডের ভাষা: ক‍্যাম্পের ভেতরে রোহিঙ্গা শরণার্থীদের…রাস্তা খুঁজে পেতে সাহায‍্য করার জন‍্য

This blog is also in English: 'Signage language: helping Rohingya refugees find their way.'

Signage in Rohingya Refugee camps feature photo

বাংলাদেশের রোহিঙ্গা শরণার্থীদের আমরা যে প্রশ্নটি করেছিলাম সেটি হলো:

“ওনে কি কেমফোর মদোতোর ঘরোর সাইনবুধগইন বুজোন্নে? ”

এই প্রশ্নটির অর্থ কি তা বুঝতে সমস‍্যা হচ্ছে?

আসলে, শুধু আপনারই সমস‍্যা হচ্ছে এমন নয়। এই প্রশ্নটি করেছি, তার মধ‍্যে ৮০% এরও বেশি লোকের এ প্রশ্নটির উত্তর দিতে সমস‍্যা হয়েছে, কিন্তু সেটি অন‍্য একটি কারণে।

একটু পরে আমরা আবার এই প্রশ্নটি দেখব। তার আগে রোহিঙ্গা শরণার্থীদের মধ‍্যে সাক্ষরতার হার কত তা জানা দরকার। রোহিঙ্গা একটি মৌখিক ভাষা, এবং যে কোনো বর্ণমালা ব‍্যবহার করেই লিখিত রূপে এ ভাষার ব‍্যবহার অত‍্যন্ত সীমিত; অংশত এ কারণে সাক্ষরতার হার এত কম। সম্প্রদায়টির মধ‍্যে সবচেয়ে জনপ্রিয় ভাষা হচ্ছে ইংরেজি, এমনকি ইংরেজির ক্ষেত্রেও আমরা সম্প্রতি যাদের সাথে কথা বলেছি তাদের মাত্র ৩১% এ ভাষাটি পড়তে পারে। আর তাদের ইংরেজি জ্ঞানও প্রাথমিক পর্যায়ের, কারণ যারা পড়তে জানেন তাদের প্রায় অর্ধেকই কেবলমাত্র সংখ‍্যা বা বর্ণ চেনেন। এই কারণে সাইনবোর্ড ব‍্যবহার করে তাদের কোনো তথ‍্য জানানো খুবই কঠিন। যে সব মানুষের তথ‍্য জানা প্রয়োজন, তাদের এমন ফরম‍্যাটে তথ‍্য দিতে হবে যা তারা বুঝতে পারে। কিন্তু লিখিত ভাষা পড়তে না পারার এই অবস্থা যদি পশ্চিমা ধরনের গ্রাফিক্স বা ছবির ক্ষেত্রেও প্রযোজ‍্য হয়? অর্থাৎ রোহিঙ্গাদের কাছে যদি তীর চিহ্ন, ইমোজি বা পিক্টোগ্রামগুলো ফরাসি বা জাপানি ভাষার মতোই কঠিন মনে হয়? তাহলে চিত্র ব‍্যবহারের মানদণ্ড এবং শব্দ কোনোটিই ব‍্যবহার না করে আমরা কিভাবে মানুষকে নির্দেশনা দেওয়ার জন‍্য ছবিভিত্তিক সংকেত ও চিহ্ন ব‍্যবহার করবো?

এখন দেখা যাক আমাদের প্রশ্নটি কী ছিল?

শুরুতে আপনাদের সামনে যে প্রশ্নটি তুলে ধরা হয়েছিলো – “ওনে কি কেমফোর মদোতোর ঘরোর সাইনবুধগইন বুজোন্নে?’ – যার অর্থ হলো: ‘আপনার ক‍্যাম্পে বিভিন্ন সেবার জন‍্য যে সাইনবোর্ডগুলো রয়েছে আপনি কি তা বুঝতে পারেন?”, জরিপকৃতদের মধ‍্যে ৬৫% (৪০৪ জনের ২৬১ জন) এর উত্তরে জোরালোভাবে বলেছেন “না!”

ক‍্যাম্পের মধ‍্যে আপনি… পথ খুঁজে পাবেন (না কি পাবেন না)

বাংলাদেশের কক্সবাজারে ছড়িয়ে ছিটিয়ে থাকা শরণার্থী ক‍্যাম্পগুলোতে এই সমস‍্যাটির প্রকৃতি অনুসন্ধান করার দায়িত্ব ছিল ট্রান্সলেটর্স উইদাউট বর্ডারসের (টিডব্লিউবি)। ২০১৭ সাল থেকে এই ক‍্যাম্পগুলোতে ৮,৫০,০০০ জনেরও বেশি রোহিঙ্গা শরণার্থী বসবাস করছে। এছাড়াও রোহিঙ্গা জনগোষ্ঠীকে সহায়তা প্রদানকারী ১৩০টিরও বেশি জাতীয় ও আন্তর্জাতিক সংস্থা ও এজেন্সি এখানে কর্মরত। প্রায় দশ লাখ মানুষ অর্থাৎ পুরো একটা শহরের সমান জনসংখ‍্যার চাহিদা মেটানো সহজ নয়। যেকোন শহরের মত এই ক্যাম্পগুলোর বাসিন্দাদেরও প্রতিদিন বিভিন্ন ধরনের সেবার প্রয়োজন হয়। কিন্তু এসব সেবার সরবরাহ-কেন্দ্র খুঁজে পাওয়াটা অনেক সময় কঠিন হতে পারে। এখানে স্মার্টফোনে গুগল ম‍্যাপ বা রাস্তার মানিচত্র দেখার কোনো সুযোগ নেই। এখানের বাসিন্দাদের ইন্টারনেট ব্যবহারের অনুমতি নেই, নেই ক্যাম্প বা রাস্তার বিশদ কোনো মানচিত্র বা ডিরেক্টরি। তাহলে, হয়তো তারা সাইনবোর্ডগুলো দেখলেই পারে। কিন্তু আপনি যদি সেটা বুঝতে না পারেন তাহলে কিভাবে ব‍্যবহার করবেন?

স্বাস্থ্যকেন্দ্র বা ক্লিনিক, খাদ্য বিতরণ-কেন্দ্র, তথ্যকেন্দ্র ইত্যাদির মত সেবা ব্যবস্থাগুলো হাজার হাজার ঘরবাড়ির মধ্যে ছড়িয়ে ছিটিয়ে রয়েছে। এগুলোতে পৌঁছতে হলে সাপের মত আঁকাবাঁকা সহস্র রাস্তা আর অলিগলির গোলকধাঁধা পার হতে হয়। এক জায়গা থেকে আরেক জায়গায় সবসময় সরলরেখায় যাওয়া যায় না, গুরুতর অবস্থায় বা জীবন-মরণের প্রশ্নে হাসপাতালে পৌঁছোবার সময়ও নয়। ক্যাম্পগুলো সাইনবোর্ড আর চিহ্নে ভরা থাকলেও সাইনবোর্ডগুলোতে রয়েছে নানা ফরম‍্যাট, ধরন, রঙ এবং বিভিন্ন ভাষার ব‍্যবহার, এগুলোর জন‍্য অনেক ক্ষেত্রেই বিভ্রান্তি সৃষ্টি হয়। একটি সমস্যা ক্যাম্পগুলোতে কর্মরত ক্যাম্প ব্যবস্থাপনা কর্মীদের চোখে পড়েছে: ক্যাম্পের অনেক বাসিন্দাই চলাফেরা করতে গিয়ে পথ হারিয়ে ফেলেন। তাঁদের মনে হয়েছে যে, গন্তব্যে পৌঁছাবার জন্য সেখানে স্পষ্ট পথ-নির্দেশক চিহ্নের প্রয়োজন। ক্যাম্পের বাসিন্দাদেরও এ বিষয়ে একই মত।

আমরা কী করেছি?

২০১৯ সালের জানুয়ারিতে, আমরা বের করি যে ক্যাম্পের সাইনবোর্ড বা নির্দেশক চিহ্নগুলোর ক্ষেত্রে সমস্যাগুলো কী। আমাদের লক্ষ্য ছিল স্থানীয় সম্প্রদায়ের সাথে মিলে এমন কিছু নির্দেশক চিহ্ন তৈরি করা যা সেখানকার বাসিন্দারা বুঝতে পারে। এক্ষেত্রে নিম্নলিখিত সেবাব্যবস্থা ও কেন্দ্রের দিকে বিশেষভাবে লক্ষ রাখা হয়েছিল:

স্বাস্থ্যসেবা কেন্দ্র/হাসপাতাল/ক্লিনিক
তথ্যকেন্দ্র
মহিলাদের জন‍্য নিরাপদ জায়গা (সেফ স্পেস)
শিশুবান্ধব স্থান
পুষ্টিকেন্দ্র
খাদ্য বিতরণকেন্দ্র

স্থানীয় সম্প্রদায়ের জানানো চাহিদা ও সুবিধার উপর ভিত্তি করে সাইট ব্যবস্থাপনা এজেন্সিগুলো যেন নির্দেশক চিহ্নের ডিজাইন তৈরির ক্ষেত্রে সমন্বিতভাবে কাজ করতে পারে তা-ই ছিল এই গবেষণার লক্ষ্য। পর্যবেক্ষণের জন্য মাঠ পর্যায়ের পরিদর্শন, ডিজাইন-পূর্ব ও ডিজাইন-পরবর্তী ফোকাস দল আলোচনা (এফজিডি), এবং সাইট ব্যবস্থাপনা সেক্টরের ওয়ার্কিং গ্রুপ ও ক্যাম্পের সব ম্যানেজারদের নিয়ে তৈরি একটি আলোচনা-দল এই গবেষণার অন্তর্ভুক্ত ছিল। আমরা নির্দেশক চিহ্নের প্রোটোটাইপের বোধগম্যতা পরীক্ষা করি, এবং একটি প্রি-পাইলট বেসলাইন স্টাডি পরিচালনা করি।

রঙ, বিষয়বস্তু ও ভাষার ক্ষেত্রে সম্প্রদায়টির পছন্দ এবং নানা রকমের আকৃতি ও লোগো সম্পর্কে তাদের জ্ঞান নিয়ে এফজিডিগুলোতে আলোচনা করা হয়। সময় ও দূরত্ব তারা কীভাবে বোঝে তা এবং বিভিন্ন প্রকার ছবির ক্ষেত্রে তাদের সংশ্লিষ্ট সাংস্কৃতিক সংবেদনশীলতা নিয়েও কথা বলে হয়। গবেষণার এই পুরো সময় জুড়ে গ্রাফিক ডিজাইনারদের সাথে নিয়ে আমরা উন্নত মানের এমন কিছু নির্দেশক চিহ্ন তৈরির চেষ্টা করেছি যা সম্প্রদায়ের সদস্যরা দেখে বুঝতে পারবে।

আরও ভাল নির্দেশক চিহ্ন কতটা দরকার তার পক্ষে-বিপক্ষে মানুষের সংখ্যা কেমন?

গবেষণার বিভিন্ন পর্যায়ে রোহিঙ্গা সম্প্রদায় থেকে জানানো হয়েছে যে, আরও উন্নত মানের নির্দেশক চিহ্ন তাদের প্রয়োজন। ২০২০ সালের জানুয়ারিতে আমরা ক্যাম্পের ৪০৪ জন বাসিন্দাকে প্রশ্ন করি যে তাঁরা ক্যাম্পের সেবা ব্যবস্থাগুলো খুঁজে বের করার সময় বর্তমানে যে সাইনবোর্ড ও নির্দেশক চিহ্নগুলো রয়েছে তা কতটা ব্যবহার করে থাকেন। আমরা দেখি যে –

৪৫% উত্তর দিয়েছেন “কখনোই না”
১২% উত্তর দিয়েছেন “খুব কম”
১৫% উত্তর দিয়েছেন “কম”
৬% উত্তর দিয়েছেন “মাঝে মাঝে”
৬% উত্তর দিয়েছেন “প্রায়ই”
১৬% উত্তর দিয়েছেন “সবসময়”।

সেবা ব্যবস্থার সাইনবোর্ড বা নির্দেশক চিহ্নগুলো পড়তে/অনুসরণ করতে কোনো সমস্যা হয় কি না তাও অংশগ্রহণকারীদের জিজ্ঞাসা করা হয়। এতে দেখা যায় –

৬০% উত্তর দিয়েছেন “হ্যাঁ”
৫% তাঁদের পরিচিতদের এমন সমস্যায় পড়তে হয়েছে বলে উল্লেখ করেছেন
৮৯% জানিয়েছেন যে, ক্যাম্পে আরও ভাল নির্দেশক চিহ্ন থাকলে সেবা ব্যবস্থাগুলো খুঁজে পেতে তাঁদের সুবিধা হবে
৯১% বলেছেন যে, আরও ভাল নির্দেশক থাকলে তাঁদের সেবাব্যবস্থা ব্যবহারের সম্ভাবনা বাড়বে।

২০১৯ সালের অক্টোবরে সম্প্রদায়ের ১৭৯ জন সদস্যকে নিয়ে পরিচালিত বোধগম্যতা পরীক্ষায় একই প্রশ্নের জবাবে ৯৭% অংশগ্রহণকারী একই জবাব দিয়েছেন। জরিপটির সময় ৯৯%-এরও বেশি (১৭৯ জনের মধ্যে ১৭৮ জন) জানিয়েছেন যে, আরও ভাল নির্দেশক থাকলে বিভিন্ন সেবা পাওয়াটা তাঁদের জন্য আরও বেশি সহজ বা সুবিধাজনক হবে।

সময়নির্দেশক চিহ্ন বা সাইনবোর্ড

নির্বাচিত ছয় প্রকার সেবাব্যবস্থার জন্য ক্যাম্পে ব্যবহৃত বিভিন্ন ফরম্যাট ও ধাঁচের নির্দেশকের নমুনা আমাদের দল থেকে পর্যবেক্ষণ করা হয় এবং সেগুলোর ছবি তোলা হয়। সেগুলোতে বেশিরভাগ ক্ষেত্রেই তথ্য শুধু লেখা হিসাবে দেওয়া ছিল, আর তাও অধিকাংশ ইংরেজিতে আর মাঝে মাঝে সাথে বাংলা এবং/বা বর্মি ভাষায় অনুবাদ। তাৎক্ষণিকভাবেই কয়েকটি প্রবণতা আমাদের দলের চোখে পড়ে:

সবচেয়ে জনপ্রিয় ভাষা হচ্ছে ইংরেজি
সাইনবোর্ডগুলোতে একটা বড় অংশ জুড়ে সংস্থাগুলোর লোগো থাকে (বাড়াবাড়ি রকমের বেশি – কোনো কোনো ক্ষেত্রে ৬টি বড় বড় লোগো রয়েছে এমনও দেখা গিয়েছে)
তীরচিহ্ন দিয়ে দিক নির্দেশ করা হয়
নির্দেশক বা সাইনবোর্ডগুলোর আনুমানিক ৮০% ইংরেজিতে লেখা এবং সেগুলোতে কোনো ছবি বা আইকন নেই (সংস্থার লোগো ছাড়া), অথচ পড়তে পারে শরণার্থীদের মাত্র ৩০%
একটি দিক নির্দেশনা অনুসরণ করে কিছুদূর যাওয়ার পর দেখা যায় সামনের গুরুত্বপূর্ণ মোড়গুলোতে আর কোনো সাইনবোর্ড নেই, যার ফলে এই দিক নির্দেশনাগুলো খুব একটা কাজে আসে না
নির্দিষ্ট করে কোনো সেবাব্যবস্থা বোঝাতে কোনো রকম ছবি বা আইকন ব্যবহার করা হয় না
নির্দেশক চিহ্নগুলোর মধ্যে মিলের খুবই অভাব, এমনকি দিক নির্দেশনা আর নির্দেশিত সেবা ব্যবস্থাগুলোর চিহ্নের মধ্যেও অসামঞ্জস্য দেখা যায়।

চারটি ক্যাম্পে পর্যবেক্ষণের ফলে আমরা নিশ্চিত হই যে, বেশিরভাগ সাইনবোর্ড বা নির্দেশক চিহ্নের নকশা যেভাবে করা হয়েছে তা রোহিঙ্গাদেরকে—বিশেষ করে, যারা খুব বেশি পড়তে পারে না বা একদমই পারে না তাদেরকে—তথ্য জানাবার জন্য উপযোগী নয়।

গবেষণাটি থেকে আমরা কী জানতে পেরেছি?

সাইট ব্যবস্থাপনা কর্মী, রোহিঙ্গা সম্প্রদায়ের সদস্য এবং গ্রাফিক ডিজাইনারদের সাথে একসাথে মিলে টিডব্লিউবি-র গবেষকরা চিহ্নগুলোর প্রোটোটাইপ তৈরি করে। এসব নির্দেশক কেমন হওয়া উচিত তা সম্পর্কে সম্প্রদায়ের বেশ কিছু পছন্দ আমরা ফোকাস দলের আলোচনা এবং অন্যান্য পরামর্শদাতার সহায়তার মাধ্যমে শনাক্ত করি।

রঙ

নির্দিষ্ট রঙ প্রায়ই নির্দিষ্ট সংস্থাকে বুঝিয়ে থাকে (যেমন- নীল রঙ জাতিসংঘকে, গোলাপি রঙ ব্র্যাককে বোঝায়)।
যারা পড়তে পারে না তাদের জন্য নির্দেশক বা সাইনবোর্ডের অর্থ বোঝার সবচেয়ে ভাল বা একমাত্র উপায় হচ্ছে রঙ দেখে চেনা, বিশেষ করে লেখার সাথে যখন কোনো ছবি থাকে না। তাই অন্তত কিছু রঙের ব‍্যবহার এখানে কাম‍্য।
সম্প্রদায় থেকে কালার কন্ট্রাস্ট বা রঙের তীব্রতার পার্থক্যযুক্ত ডিজাইনের প্রতি পছন্দের কথা জানানো হয়েছে — গাঢ় রঙের পটভূমির উপর-হালকা রঙের লেখা/ছবি দেখা/পড়া সহজ হয়।
চূড়ান্ত প্রোটোটাইপের পরীক্ষার সময় ১০০% অংশগ্রহণকারীই (১৭৯ জন) মূল ছবির চারদিকে রঙিন সীমানা আঁকা থাকলে ভাল হয় বলে জানিয়েছেন।

কোথায় এবং কখন

ফোকাস দলে অংশগ্রহণকারীদের মধ্যে তীরচিহ্নের প্রতি সন্তুষ্টি দেখা যায় নি।
তাঁরা জানিয়েছেন যে, আঙুল দিয়ে দিক নির্দেশ করা হলে তা তাঁরা বেশি পছন্দ করবেন।
- চিহ্নগুলোর প্রোটোটাইপের চূড়ান্ত পরীক্ষার সময় অংশগ্রহণকারীদের ৯৩% আঙুলের ছবি দিয়ে নির্দেশিত দিক সঠিকভাবে সনাক্ত করতে পেরেছেন।
- ৭৬% অংশগ্রহণকারী জানিয়েছেন যে, গন্তব্যে পৌঁছে গেছেন বোঝাতে পাশাপাশি খোলা দুই হাতের ছবির পরিবর্তে নিম্নমুখী আঙুলের ছবি বেশি ভালো।
গন্তব্যে পৌঁছতে কত মিনিট লাগবে তা বোঝানো বেশ কষ্টসাধ্য বলে দেখা যায় – নানা রকম প্রচেষ্টার পরও উল্লেখযোগ্য ফল আসে নি।
অংশগ্রহণকারীদের সাক্ষরতা অনুযায়ী, চূড়ান্ত প্রোটোটাইপ পরীক্ষায় ৫৪% অংশগ্রহণকারী প্রতিটি গন্তব‍্য পৌঁছানোর হন‍্য কতটুকু সময় লাগবে তা বুঝতে পেরেছেন।

ভাষা

বলা বাহুল্য, লেখা শুধু তাদেরই কাজে আসে যারা পড়তে পারে।

লিখিত ভাষার মধ‍্যে বর্মি ও ইংরেজি সবচেয়ে বেশি মানুষ বুঝতে পারে।
সম্প্রদায়টির একটি বিশাল অংশই বাংলা পড়তে পারে না। কর্তৃপক্ষও সাইনবোর্ড বা নির্দেশক চিহ্নে বাংলা ভাষা ব্যবহারের পক্ষপাতী নয়।

ফরম‍্যাট

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জনপ্রিয় নয় এমন ধরনের ছবি;
অংশগ্রহণকারীদের পছন্দ বাস্তবসম্মত আঁকা ছবি

ছবির নানাবিধ প্রকারের মধ্যে সেবা গ্রহণরত মানুষের বাস্তবসম্মত আঁকা ছবিই সবচেয়ে বেশি জনপ্রিয়।
প্রোটোটাইপের পরীক্ষার সময় যাঁদের পরামর্শ নেওয়া হয়েছে তাঁদের ৮৩% বলেছেন যে, সাইনবোর্ড বা নির্দেশকে ছবি/কার্টুন এবং লেখা—দুটোর একসাথে থাকাটাই তাঁদের বেশি পছন্দ।
৩%-এরও কম কেবল লেখা (বর্ণ/বাক্য) থাকলে ভাল হবে বলেছেন।
তোলা ছবি (ফটোগ্রাফ) জনপ্রিয়তা পায় নি (৮৯.৪% বলেছেন তোলা ছবি তাঁদের পছন্দ নয়)।
মানুষের ছবির সরল রূপ (বা ইমোজির মত রূপ) বিভ্রান্তি সৃষ্টি করেছে, অংশগ্রহণকারীদের অনেকেই বলেছেন সেগুলোকে তাঁদের ভূত বলে মনে হয়।
অংশগ্রহণকারীদের নব্বই শতাংশ জানিয়েছেন যে, তাঁরা সাধারণত ছবি দেখে কোনো সাইনবোর্ড বা নির্দেশকের অর্থ বোঝার চেষ্টা করে থাকেন।

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অবশেষে উন্নতির লক্ষণ দেখা যাচ্ছে!

মহিলাদের জন‍্য নিরাপদ স্থান: আমাদের অন‍্যতম একটি প্রোটোটাইপ

টিডব্লিউবির গবেষকদের সাথে কর্মরত আমাদের গ্রাফিক ডিজাইনাররা সমাধান হিসাবে এই চিহ্নটি ব‍্যবহার করতে পরামর্শ দিয়েছেন। ক্যাম্পের রোহিঙ্গা বাসিন্দাদের পছন্দ ও চাহিদার উপর ভিত্তি করে তৈরি ছয়টি নির্দেশকের মধ্যে এটি একটি। এই নকশায় সম্প্রদায়ে পরীক্ষিত সচিত্র যোগাযোগ পদ্ধতি (জীবন্ত চিত্র, আঙুলের সাহায‍্যে দিক নির্দেশনা) ব‍্যবহার করার সাথে সাথে যারা পড়তে পারেন তাদের জন‍্য বর্মি ও ইংরেজি ভাষায় তথ‍্য সংযুক্ত করা হয়েছে। চিহ্নগুলোকে দেখতে খুব সাধারণ মনে হলেও, এগুলো সম্প্রদায়টির জটিল ও সুনির্দিষ্ট চাহিদাগুলো সামনে রেখে তৈরি করা হয়েছে।

এই চিহ্নগুলির চূড়ান্ত প্রোটোটাইপ পরীক্ষার সময় সম্প্রদায়ের যেসব সদস্যের সাথে কথা বলা হয়েছে তাঁদের সবাই বলেছেন যে, এই ফরম্যাট মেনে ক্যাম্পে সাইনবোর্ড বা নির্দেশক লাগানো হলে তা তাঁদের জন্য সহায়ক হবে (৯৭% “অনেক সহায়ক”, ৩% “সহায়ক”)। চারটি ক্যাম্পে উল্লিখিত ছয়টি সেবা ব্যবস্থার সাইনবোর্ড বা নির্দেশক নিয়ে প্রারম্ভিক পরীক্ষার (পাইলট টেস্ট) প্রস্তুতি চলছে, আর এই ফলাফল পাওয়ার প্রত্যাশিত সময় ২০২০ সালের মাঝামাঝি।

আশা করা যায় এবার রোহিঙ্গা শরণার্থীরা ক‍্যাম্পের ভেতরে পথ খুঁজে পাবেন!

Peter Squires, Evidence and Impact Officer for the Rohingya Response, Translators without Borders

Clarity is the overlooked opportunity in the rush to produce COVID-19 information

Clarity is an important but often overlooked factor in COVID-19 communication. The World Health Organization, UNHCR, and the Centers for Disease Control emphasize the importance of clarity in health communications. These and other agencies urge us to use established plain-language principles to achieve that required clarity.

The great benefit of plain language is that it requires a relatively low reading effort to understand and be able to use the information. It helps all of us, regardless of our socioeconomic or educational status, professional skills, linguistic ability, or literacy level. In a crisis, we are all anxious, rumors are common, and timing is critical. We all want to have and to offer certainty. In the COVID-19 pandemic, plain language has the potential to change behavior, overcome rumors, and ultimately to save lives. We should use it more than we currently do.

We can and should communicate more clearly, and plain language shows us how to do that

Many documents that Translators without Borders receives from humanitarian organizations don’t follow basic plain-language principles. That’s a missed opportunity, not just in how we communicate with communities. It’s also a missed opportunity to communicate more effectively with our colleagues, donors, boards, governments and other partners. Plain language can revolutionize how we communicate in general.

I recently reviewed and edited 10 documents that 10 humanitarian organizations produced as part of their COVID-19 response. All organizations sent the documents to Translators without Borders as final versions ready for translation and distribution.

Each of the documents contains multiple opportunities to add clarity for readers. Several even contain spelling and grammatical errors. In isolation, individual issues and examples can seem pedantic. But collectively they highlight an opportunity for us to communicate more effectively.

I identified five relatively easy ways to improve document clarity. Writers should use:

active voice
short sentences
correct terminology
consistent terminology
concise wording.

Use the active voice

The active voice is clearer than the passive voice because it specifies who is responsible for an action. That helps our readers to be accountable for their actions; it also allows them to hold us accountable. The active voice typically uses fewer words, leading to shorter sentences. It also makes the verb more dominant, which focuses the reader’s attention on the relevant action.

Despite those obvious advantages, passive voice is an issue in eight of the 10 documents. Two documents contain 25% or more sentences in the passive voice. Two others include passive voice in more than 18% of sentences.

Use short sentences

Sentence length influences reader comprehension. A general plain-language recommendation is to limit sentences to 20 words or fewer, although most readers can comprehend longer sentences. Longer sentences require simple syntax and grammatical structures to help the majority of readers understand them. But rather than expect untrained writers to use simple syntax and grammatical structures, it’s easier to suggest they use short sentences.

Long sentences are an issue in eight of the 10 documents I reviewed. They use multiple complex sentences with up to 50 words. The complex opening sentence of one document contains 42 words, several clauses, various tenses, and multiple verbs. It also addresses several ideas:

“In several countries and on global level, persons with disabilities have spoken out that government information is not being shared in accessible formats or that measures are not made to compensate for reduction in support services that persons with disabilities depend on.”

A plain-language alternative with 33 words in three simple sentences is:

“Many persons with disabilities have said that they are not adequately supported by their government. Some governments don’t provide information in accessible formats. Others don’t compensate well enough for reduced disability support services.”

Use key terms correctly

A clear document saves your reader having to assume or infer any information. That’s important because incorrect assumptions and inferences can cause misunderstandings and rumors. Misused or unclear terms also undermine your credibility as a trusted information source.

Three of the 10 documents that I reviewed use a significant term incorrectly. They incorrectly assert that COVID-19 is a type of coronavirus. The actual message we need to convey is that COVID-19 is the disease caused by a type of coronavirus.

Several of the other documents use “coronavirus” and “COVID-19” interchangeably. Errors or oversights like this confuse readers, and require them to apply extra reading effort to untangle the true meaning.

Use terminology consistently

Synonyms confuse readers. So a key plain-language principle is to use one term to describe one concept. That increases reader understanding, which is a critical aspect of changing readers’ behavior. In the 10 documents I reviewed, the majority used multiple terms to refer to the same concepts.

For example, some documents use both “separate” and “isolate” to refer to the same concept. Others use “the disease” and “the illness” to mean the same thing. One document uses “germ” and “virus” to mean the same thing.

All of these pairs are legitimate synonyms. In some contexts readers might even view such variation as a sign of creativity. But in an urgent humanitarian response, always choose clarity over creativity.

Use concise wording

Use the minimum number of words to make your point. It’s a fundamental plain-language principle and a powerful way to engage your readers and keep their interest.

One document uses 47 words to explain how to wipe a surface:

“Bleach usually comes in a 5% solution. Add cold water (hot water will not work) to dilute it, using 2 cups of bleach in a 5 gallon bucket of water. First clean with soap and water, then clean with the bleach solution and let it air dry”

A more concise 28-word alternative is:

“Clean surfaces with soap and water. Then wipe the surfaces with a mix of 2 cups of household bleach in 5 gallons of cold water.”

Let’s clear up the confusion and the rumors

The urgent and changeable nature of the COVID-19 response partly explains the lack of clarity in the 10 documents. But it doesn’t make it excusable, especially given the ongoing concerns among responders about uncertainty, rumors, misinformation, confusion, and undesirable behavior. Plain-language writing offers a way for all of us to communicate more clearly. We should all try to understand it better and apply it more consistently.

Written by Kate Murphy, Plain Language Editor for Translators without Borders