At Translators without Borders (TWB), we are lucky to have extraordinary team members who are recognized worldwide. We are always grateful to have uniquely skilled members of the international community choose to be part of our cause. Today, we are proud to share the story of Cédrick Irakoze, Crisis Response and Community and Recruitment Intern for TWB. He was recently awarded a place to be part of the Young African Leaders Initiative (YALI) network. The YALI network invests in the next generation of African leaders, providing invaluable opportunities to connect and learn from experts. Learn more about the YALI network here.
Cédrick is a young Burundian language professional. He holds a bachelor’s degree in TESOL (Teaching English to Speakers of Other Languages) from the University of Burundi, and has years of experience as a professional translator. He believes that language can improve or even save lives in this global world. And interaction in the right language can be vital for everyone, no matter people’s language, culture, or the color of their skin.
“TWB is my professional home” – Cédrick
In 2018, Cédrick first featured in our blog as a volunteer translator from English and French into Rundi. This was his introduction to the world of language in humanitarian work: “When I joined TWB as an intern, I joined a community of like-minded individuals serving the global community. Now I call TWB my professional home.” Day-to-day, Cédrick engages and collaborates with our translator community to help create a world with no language barriers.
But in late 2019, he did something different. He successfully applied for the Young African Leaders Initiative program.
The Young African Leaders Initiative (YALI)
In 2016, Cédrick joined the Young African Leaders Initiative network with over 25,000 other young and talented individuals. In 2019, he met with 108 successful candidates from over 7000 applicants to attend a one-month leadership training course.
A group of YALI network members in Nairobi.
Energetic public officials, business owners, and local and international nonprofit leaders from all over Africa came together in Nairobi, Kenya. On hearing their stories, Cédrick reflected, “The way they are each committed to making their communities better inspired me.” The Translators without Borders team is delighted to have witnessed a team member take on such an exciting, formative challenge.
“Thank you very much. TWB showed me so much love and support before and during the program!” – Cédrick
Cédrick Irakoze, right, with TWB Kenya Manager Paul Warambo, left.
It’s all about communication
The course was about inspiring and equipping one another to become better leaders. Participants developed their communication skills and built solutions-oriented networks. These factors are central to the changes these young leaders want to see in society. Each member of the diverse group – native speakers of over fifty languages – played a vital part.
Cédrick Irakoze, left presenting to the YALI network members.
This richness and diversity are reflected in TWB’s own community of translators and supporters, and in our way of working. We too rely on the power of teamwork to make change — to improve communications and access to information worldwide. Cédrick’s big takeaway is that when we come together we can innovate, we can flourish and we can make each other feel valued.
“Diversity is richness in professional life” – Cédrick
With the skills he’s learned through this course, Cédrick hopes to make a positive impact in his professional and social circles. “I can’t wait to contribute more and better to our common mission: to create a world that knows no language barriers.”
Cédrick Irakoze and friends at the YALI network meetup in Nairobi.
Written by Danielle Moore, Communications Officer for Translators without Borders. Interview responses by Cédrick Irakoze, Crisis Response and Community and Recruitment Intern for Translators without Borders.
Translators improve lives by translating potentially lifesaving information into languages spoken by vulnerable individuals. Those who volunteer as part of the Translators without Borders (TWB) Community have a range of experiences and skills. They share our vision of a world where knowledge knows no language barriers. We are grateful for all our translators, and we love sharing their stories.
Shared philosophies
Irina’s philosophy fits right in with that of Translators without Borders: “In our information-packed society, it is essential to maintain access to vital information for everybody. So, my biggest motivation is helping people by delivering information to interested parties,” says Irina, former lawyer now turned English-Russian translator. Since joining as a volunteer translator in 2016, Irina has translated and revised a total of 110,220 words into Russian, one of our top ten most frequently requested languages.
Irina Nosova, translator
The projects touch on all sorts of information, including healthcare. Often, information and research in one language benefit speakers of another language – but it needs to be accurate and it needs to be available. So we asked about a particular project which made vital information available in Irina’s own country, in Russian, her mother-tongue. When tasked with translating an important anti-tuberculosis study she found it to be one of her most difficult projects to date. The translator translated study protocol and presentations to find out more, before later reading news articles and discovering the reality of the tuberculosis situation in Russia.
“I was shocked to find how high the burden of tuberculosis is in my country!” – Irina
Finding practical solutions
Although Irina focuses on the importance of language in Russia, she is also hopeful about how sharing information in many languages can spread helpful and life-changing information. “I hope that the study of novel tuberculosis treatment will speed up the registration of new drugs which are vital for successful treatment,” she told TWB.
As well as more academic pieces, Irina finds translating personal stories equally important. One of her projects involved translating patients’ stories for partner non-profit EURORDIS – Rare Diseases Europe.
“I realized that stories shared by patients with rare diseases and their families could inform people in similar situations in Russia about how to deal with those diseases.” – Irina
Tapping into your skillset
Irina’s desire to help as a volunteer translator has helped her tap into personal and professional skills. “Volunteering improved my time management: I have to calculate and allocate the time I can spend to complete the tasks before the deadline, alongside my other daily tasks. Before launching my own business, I worked as a lawyer and I volunteered with TWB at night, after work. Now, I can be more flexible and am able to contribute more time.”
Her advice for other TWB Community members is to constantly improve your skills, learn new terminology, and check your quality of translation. “Doing translation in Kató – TWB’s online translation environment – requires the same quality approach as any other project: the highest possible. So, before claiming the new task make sure you understand the topic and do your own research to provide the best possible translation.” It helps you understand the context and importance of the situation you are translating about – like in the case of Irina’s tuberculosis project. When Irina dug deeper into the topic she was translating about, she discovered a personal interest in medical translation and later, clinical research. Her projects opened new doors: “Volunteering with TWB improved my resourcefulness and research skills and pushed me to explore new horizons in translation, take new courses, and dig deeper.”
TWB’s current research focuses on bringing language technology to marginalized communities
Translators without Borders (TWB) aims to empower people through access to critical information and two-way communication in their own language. We believe language technology such as machine translation systems are essential to achieving this. This is a challenging task given many of the languages we work with have little to no language data available to build such systems.
In this post, I’ll explain some methods for dealing with low-resource languages. I’ll also report on our experiments in obtaining a Tigrinya-English neural machine translation (NMT) model.
The progress in machine translation (MT) has reached many remarkable milestones over the last few years, and it is likely that it will progress further. However, the development of MT technology has mainly benefited a small number of languages.
Building an MT system relies on the availability of parallel data. The more present a language is digitally, the higher the probability of collecting large parallel corpora which are needed to train these types of systems. However, most languages do not have the amount of written resources that English, German, French and a few other languages spoken in highly developed countries have. The lack of written resources in other languages drastically increases the difficulty of bringing MT services to speakers of these languages.
Low-resource MT scenario
In scientific literature for machine translation, there is no particular consensus on which corpus size constitutes a low-resource scenario. But we can say roughly that a low-resource condition is when the size of the parallel training corpus is not sufficient for reaching an acceptable result with the standard MT approaches. This is usually judged with a standardized automatic evaluation metric called BLEU, which correlates with human translation assessments.
Figure 2, modified from Koehn and Knowles (2017), shows the relationship between the BLEU score and the corpus size for the three MT approaches.
A classic phrase-based MT model outperforms NMT for smaller training set sizes. Only after a corpus size threshold of 15M words, roughly equivalent to 1 million sentence pairs, classic NMT shows its superiority.
Low-resource MT, on the other hand, deals with corpus sizes that are around a couple of thousand sentences. Although this figure shows at first glance that there is no way to obtain anything useful for low resource languages, there are ways to leverage even small data sets. One of these is a deep learning technique called transfer learning, which makes use of the knowledge gained while solving one problem to apply it to a different but related problem.
Cross-lingual transfer learning
Zoph et al. (2018) applied transfer learning in machine translation and proved that having prior knowledge in translation of a separate language pair can improve translating a low-resource language.
Figure 3 illustrates their idea of cross-lingual transfer learning.
The researchers first trained an NMT model on a large parallel corpus — French–English — to create what they call the parent model. In a second stage, they continued to train this model, but fed it with a considerably smaller parallel corpus of a low-resource language. The resulting child model inherits the knowledge from the parent model by reusing its parameters. Compared to a classic approach of training only on the low-resource language, they record an average improvement of 5.6% BLEU over the four languages they experiment with. They further show that the child model doesn’t only reuse knowledge of the structure of the high resource target language but also on the process of translation itself.
The high-resource language to choose as the parent source language is a key parameter in this approach. This decision is usually made in a heuristic way judging by the closeness to the target language in terms of distance in the language family tree or shared linguistic properties. A more sound exploration of which language is best to go for a given language is made in Lin et al. (2019).
Multilingual training
The path that was cleared by cross-lingual transfer learning led naturally to the use of multiple parent languages. The straightforward approach, first described by Dong et al. (2015), mixes all the available parallel data in the languages of interest and sends them into training as illustrated in Figure 4.
What results from the example is one single model that translates from the four languages (French, Spanish, Portuguese and Italian) to English.
Multilingual NMT offers three main advantages. Firstly, it reduces the number of individual training processes needed to one, yet the resulting model can translate many languages at once. Secondly, transfer learning makes it possible for all languages to benefit from each other through the transfer of knowledge. And finally, the model serves as a more solid starting point for a possible low-resource language.
For instance, if we were interested in training MT for Galician, a low-resource romance language, the model illustrated in Figure 4 would be a perfect fit as it already knows how to translate well in four other high-resource romance languages.
A solid report on the use of multilingual models is given by Neubig and Hu (2018). They use a “massively multilingual” corpus of 58 languages to leverage MT for four low-resource languages: Azeri, Belarusian, Galician, and Slovakian. With a parallel corpus size of only 4500 sentences for Galician, they achieved a BLEU score of up to 29.1% in contrast to 22.3% and 16.2% obtained with a classic single-language training with statistical machine translation (SMT) and NMT respectively.
Transfer learning also enables what is called a zero-shot translation, when no training data is available for the language of interest. For Galician, the authors report a BLEU score of 15.5% on their test set without the model seeing any Galician sentences before.
Case of Tigrinya NMT
Tigrinya is an Ethiopian language spoken by around 7.9 million people in Eritrea and Ethiopia. It is neither supported by any commercial MT provider, nor has any publicly available models. TWB is currently developing open datasets and MT for Tigrinya in cooperation with the Masakhane initiative.
Tigrinya is no longer in the very low-resource category thanks to the recently released JW300 dataset by Agic and Vulic. Nevertheless, we wanted to see if a higher resource language could help build a Tigrinya-to-English machine translation model. We used Amharic as a parent language, which is written with the same Ge’ez script as Tigrinya and has larger public data available.
The datasets that were available to us at the time of writing this post are listed below. After JW300 dataset, the largest resource to be found is Parallel Corpora for Ethiopian Languages.
Our transfer-learning-based training process consists of four phases. First, we train on a dataset that is a random mix of all sets totaling up to 1.45 million sentences. Second, we fine-tune the model on Tigrinya using only the Tigrinya portion of the mix. In a third phase, we fine-tune on the training partition of our in-house data. Finally, 200 samples earlier allocated aside from this corpus are used for testing purposes.
As a baseline, we skip the first multilingual training step and use only Tigrinya data to train on.
We see a slight increase in the accuracy of the model on our in-house test set when we use the transfer learning approach. The results in various automatic evaluation metrics are as follows:
Conclusion
Neural machine translation is a data-hungry technology. Although this severely reduces the possibility to expand it to the majority of the world’s languages, we can still apply various techniques to make it available to more people than if we limited ourselves to approaches tuned towards high-resource languages. Methodologies like transfer learning and linguistically informed data mixture have a role to play in helping everyone communicate in their language.
Written by Alp öktem, Computational Linguist for Translators without Borders
Written by Alice Castillejo, Programme Advisor for Translators without Borders
For every new response, we need the right words to fight sexual abuse
I work for Translators without Borders, an organization that highlights the importance of language and clear communication. I am blessed to work with colleagues who expose me every day to subtle linguistic and cultural differences. Some of those differences result in hilarious misunderstandings, others are more challenging. They always point to the importance of choosing our words with care.
I was reminded of that again last week when I stood in front of a room full of my multicultural professional peers to discuss sexual abuse. I suddenly found myself acutely aware of the need to get my words right to avoid embarrassing myself or offending the audience.
100 Translations to Prevent Sexual Exploitation and Abuse
Understanding what sexual exploitation and abuse mean in a humanitarian emergency is not as simple as it seems. For local staff, who may never have worked for humanitarian organizations before, it can be even more complicated. Principles aimed at preventing sexual exploitation and abuse contain new ideas about power relationships, new terms to understand, and new rules and responsibilities to learn and put into practice. Providing the information in a language that local staff can understand is the least we can do and an important first step toward addressing the problem.
In collaboration with the UN’s Inter-Agency Standing Committee (IASC), Translators without Borders (TWB) developed a plain-English version of the key humanitarian messages on preventing sexual exploitation and abuse. The benefit of a plain-English version is twofold:
It promotes wider understanding, particularly among those with limited English proficiency.
It removes ambiguity and legal terminology, increasing the chances of an accurate translation into other languages. For example, we replaced legalese like “constitute acts of gross misconduct and are therefore grounds for termination of contract” with “humanitarian workers can be disciplined – even fired – for unacceptable behavior in relation to sex”.
Distribution of the 100 Translations
We then translated the plain-English version into more than 100 languages, and started to distribute them to communities around the world.
A sudden-onset crisis often mobilizes people who have never thought about sexual abuse or power dynamics in their regular day jobs. The new local staff may come from a context where going to sex workers is commonplace, or where informal exchanges and bribes, including transactional sex, are part of getting things done. And often they live in a hierarchy where reporting one’s peers or seniors is dangerous.
We need to explain in clear language that these practices are forbidden in the humanitarian context, and that staff must report them. In translation, there are compromises in this process – is it better to find a word with no stigma or a word that will be more widely understood? For example, while the term “sex worker” is a more empowering term, we found that “prostitute” is more widely understood, despite its negative connotations. And if terms are gendered, have we chosen words that clearly indicate that sexual abuse may include sexual abuse of men? Are we sure the words we’ve chosen are neither so crude that they offend nor so euphemistic that they are incomprehensible?
Working with Partners to Ensure the 100 Translations are Effective
Since the launch of this joint IASC-TWB project in 2018, TWB’s team of translators and supporters has worked hard to produce accurate translations, which have then been reviewed and validated by local humanitarian staff from across the world. Our local reviewers have played an essential role, offering specific local terms, checking suitability, and adjusting translations to reflect local dialect. That is why, for example, we have several Arabic and Spanish language versions, as well as audio versions for Rohingya and Chittagonian.
We know that 100 languages is a drop in the ocean. But for each new multilingual humanitarian crisis, we hope to build the portfolio to meet the needs of newly engaged humanitarian staff.
How to start using the 100 Translations to Prevent Sexual Exploitation and Abuse
The key messages are just a start. Crisis-affected communities need to understand what behaviour from humanitarians is unacceptable. We may need to deliver the message in more hard-to-source languages and also in audio or pictorial formats. Staff training packages must be in languages that staff understand. And, of course, when someone is exploited or abused, they must be able to report in the language they are most comfortable in and receive support in that language.
You can help make sure that humanitarians understand what Protection from Sexual Exploitation and Abuse (PSEA) is and what it means for them. Please join us in this effort by distributing the translations to your colleagues, making sure your training is in languages they truly understand, and providing new translations in additional languages.
You can find more information about this project, and the growing number of translations, here.
The Core Humanitarian Standard Commitments are now available in plain English
Written by Kate Murphy, Plain-language editor for Translators without Borders, and Ellie Kemp, Head of Crisis Response for Translators without Borders.
Translators without Borders (TWB) helps its humanitarian partners apply plain language principles to written content. We worked together with the CHS Alliance to develop a plain-language version of the Core Humanitarian Standard’s Nine Commitments.
As humanitarians, we use tools like the Core Humanitarian Standard on Quality and Accountability (CHS) to hold ourselves accountable to the people we assist. We know that the best responses are those shaped by those directly affected. The CHS provides a great opportunity to institutionalise Accountability to Affected Populations in a way that effectively translates at field level for our work.
But ironically, many of the people we assist themselves aren’t yet aware of our commitments to them. Many don’t have the literacy skills to read, understand, or react to them. Others simply won’t have the time, motivation, or emotional energy to read through the full Nine Commitments of the CHS.
Teacher writing sentences in Rohingya Zuban (Hanifi Script). Kutupalong Refugee Camp near Cox’s Bazar, Bangladesh. Photo: Eric DeLuca / Translators without Borders
The question for CHS Alliance was how to make information on quality and accountability accessible to the affected population. Could plain language help everyone to hold aid organisations to account, in line with CHS Commitment 4? TWB jumped at the chance to help with this. For us, it was another opportunity to highlight the importance of communicating with people in an appropriate and usable language and format.
Everyone appreciates plain language
Plain language makes text easier to understand, easier to put into practice, and easier to recall later. For English materials, such as the new CHS onepager, this means using plain-English. Non-native English speakers appreciate it, especially those with limited education and limited English language skills. But highly literate speakers also benefit, especially those operating in high-pressure environments. And of course, it makes translation easier too.
That’s the thing about plain language: everyone who appreciates clear, concise information benefits from it.
Plain language reduces that reading effort for everyone.
To make the CHS Commitments easier to read, we helped the CHS Alliance apply three established plain-language principles:
Use personal pronouns, including “you” and “we.” That engages readers and adds certainty about who is responsible for different actions.
Rewrite sentences so they contain fewer than 20 words. Shorter sentences are easier to comprehend.
Replace uncommon or technical terms with alternatives that are familiar to all readers.
Photo credit TWB.
We used word-frequency data to identify words in the CHS Commitments that occur less commonly in English print and audiovisual media. The more frequently a term occurs in different media, the more likely it is to be familiar to readers. So, we replaced less frequent words with more common alternatives. For instance, we replaced ‘assistance’ with ‘support’.
Some words like “resilient,” “entitlements,” “competent,” and “efficiency,” are included in the original CHS Commitments, and experienced humanitarians are likely to comprehend them easily. However, word-frequency data suggests that they may reduce reading speed and therefore reader engagement for people who are less familiar with them. Because we wanted to reduce general reading effort, we replaced them.
Spread the word
CHS Alliance members and partner organisations can access the plain language English version of the CHS commitments. Over the coming months, the CHS Alliance expects to provide translated versions in an increasing number of languages and will keep you updated on progress.
In the meantime, CHS Alliance members who are part of the new AAP Community of Practice have suggested various ways we could use the plain-English version to communicate our commitments more effectively to affected people:
Provide an audio version of the plain-English commitments for less literate audiences.
Develop graphics to accompany the text and make it available as a poster or leaflet.
Develop a child-friendly version.
Provide staff with guidance on how to use the plain-English version as part of accountability to affected populations.
Agree a common way to track understanding of the plain-language versions, possibly as part of regular perception and satisfaction monitoring activities.
We’re excited to see how the new plain-language CHS will help make accountability a reality for all those we serve.
What do you think?
To find out more about how plain language could benefit your organization please get in touch with Kate Murphy, Plain-language editor at [email protected].
We recently held our very first translation contest for Translators without Borders’ thriving community of Arabic translators. Ninety-two talented translators submitted a total of 124 translations on a mixture of humanitarian and literary topics. Each translation was evaluated by fellow community members for accuracy, terminology, and style in order to provide constructive feedback and create greater engagement among the Arabic community.
The winners: humanitarian translation
Shaimaa Elhosan is an English to Arabic translator specializing in humanitarian translation because of her desire to help others. She studied UN translation at the American University in Cairo, which helped her follow her passion.
“I want to help other people, especially children, victims of conflicts, and abused women, people affected by natural disasters. Thus, I volunteered with Translators without Borders (TWB).”
A career highlight as a freelance translator was working on a book titled The Happy Healthy Nonprofit, by Beth Kanter and Aliza Sherman. At that point, Shaimaa realized what a leading role nonprofits play in improving difficult situations.
Shaimaa Elhosan, Arabic translator for TWB
The first story she encountered with TWB was poignant: it told of the daily suffering of victims of war. And it highlighted the misleading images of a comfortable life in camps which too often circulate on social media.
Since 2017, Shaimaa has used her skills to translate 8,951 words for TWB and has acquired more valuable experience in humanitarian translation in the process. She continues to study in a constant effort to improve and expand her knowledge.
“I study because I care so much about whether or not the translation communicates the meaning clearly to readers. The TWB team appreciates my know-how and they ask me to participate in more projects. They try hard to support us in translation by providing references and glossaries as much as possible.”
Shaimaa explained that the challenge of communication was made more exciting by this competition. “How could I render the meaning to the readership clearly with such a tricky text? The experience spurred me on to participate in more projects. I’d like to continue to support displaced people, children, and abused women with my work.”
Literary translation
Nabil Salibi won the literary translation category, having received the highest score from his fellow community members.
Graduation photo from Nabil’s Masters in Interpreting and Translating, 2018
This professional translator is as dedicated to his volunteer projects as he is to his paid work. By volunteering, he hopes to bridge the communication gap between humanitarian organizations and those who seek their support. For Nabil, this means dedicating four to five hours at a time to translate or proof-read texts from his home in Australia.
Since joining TWB in 2016, Nabil has translated 13,592 words. He has focused on projects related to refugees and the conditions in refugee camps, as well as news articles. Nabil also helped translate IFRC’s Global Response Tools Review. That review analyzed the tools we use to respond to disasters, and the risks and challenges related to humanitarian response. He takes each of these projects seriously:
“Volunteering allows me to appreciate the difficulties imposed by language barriers and the impact on the wellbeing of people who live in communities where they don’t understand the local language.”
Numerous other translators earned honorable mentions for their efforts. Learn more about their work, and the translation process on the Kató Community Forum.
A shared reward: the language equality initiative
Our highly skilled translators, including Nabil and Shaimaa, will have the opportunity to contribute to Gamayun, the language equality initiative. The goal is to shift control of communication, to allow everyone to share their voice and access information in a language and format they can understand. Using advanced language technology, we’re working with marginalized communities and language specialists to increase language equality and improve two-way communication. Over half of the world’s population simply doesn’t have access to knowledge and information in their own language. Our translators and supporters address this language gap which can prevent people from lifting themselves out of poverty, getting health care, recovering from a crisis, or understanding their rights. Our translators’ efforts enable people to proactively share their needs, concerns, and ideas.
We recently announced two new translation contests open to our French and Swahili translator communities. If you are already a TWB translator please check the Kató Community Forum for more information. Otherwise, why not join TWB today so you can take part? Entries close on 5 August 2019.
In case you’re looking to take part in a contest, or improve your own translations, our first translation contest winners share some words of advice:
“Make sure you understand the whole article. Context is key.” – Nabil
“I love to translate on paper first.” – Nabil
“Never stop reading.” – Shaimaa
Written by Danielle Moore, Communications Officer for Translators without Borders.
Interview responses by Shaimaa Elhosan and Nabil Salibi, Translators for
Translators without Borders.
“Sir, I want to ask you some questions if you agree?”
With that one sentence, our enumerator summarized the 120-word script provided to secure the informed consent of our survey participants – a script designed, in particular, to emphasize that participation would not result in any direct assistance. Humanitarian organizations, research institutes and think tanks around the world are conducting thousands of surveys every year. How many suffer from similar ethical challenges? And how many substandard survey results fall under the radar due to lack of effective quality assurance?
We were conducting a survey on the relationship between internal displacement, cross-border movement, and durable solutions in Borno, a linguistically diverse state in northeast Nigeria. Before data collection began, Translators without Borders (TWB) translated the survey into Hausa and Kanuri to limit the risk of mistranslations due to poor understanding of terminology. Even with this effort, however, not all the enumerators could read Hausa or Kanuri. Although enumerators spent a full day in training going through the translations as a group, there is still a risk that language barriers may have undermined the quality of the research. Humanitarian terminology is often complex, nuanced, and difficult to translate precisely into other languages. A previous study by Translators without Borders in northeastern Nigeria, for example, found that only 57% of enumerators understood the word ‘insurgency’.
We only know the exact phrasing of this interview because we decided to record some of our surveys using an audio recorder. In total, 96 survey interviews were recorded. Fifteen percent of these files were later transcribed into Hausa or Kanuri and translated into English by TWB. Those English transcripts were compared to the enumerator-coded responses, allowing us to analyze the accuracy of our results. While the process was helpful, the findings raise some important concerns.
A digital voice recorder in Maiduguri, Nigeria serves as a simple and low-tech tool for capturing entire surveys. Photo by: Eric DeLuca / Translators without Borders
Consent was not always fully informed
Efforts to obtain informed consent were limited, despite the script provided. According to the consultant, enumerators felt rushed due to the large numbers of people waiting to participate in the survey – but people were interested in participating precisely due to the misbelief that participation could result in assistance, which underlines the need for informed consent.
Alongside these ethical challenges, the failure to inform participants about the objectives of the research increases the risk of bias in the findings, prompting people to tailor responses to increase their chances of receiving assistance. Problems related to capacity, language, or questionnaire design can also negatively impact survey results, undermining the validity of the findings.
The enumerator-coded answers did not always match the transcripts
During data quality assurance, we also identified important discrepancies between the interview transcripts and the survey data. In some cases, enumerators had guessed the most likely response rather than properly asking the question, jumping to conclusions based on their understanding of the context rather than respondents’ lived experiences. If the response was unclear, random response options were selected without seeking clarification. Some questions were skipped entirely, but responses still entered into the surveys. The following example, comparing an extract of an interview transcript with the recorded survey data, illustrates these discrepancies.
Interview transcript
Survey data
Interviewer: Do you want to go back to Khaddamari?
Respondent: Yes, I want to.
Interviewer:When do you want to go back?
Respondent: At any time when the peace reigns. You know we are displaced here.
Interviewer:If the place become peaceful, will you go back?
Respondent: If it becomes peaceful, I will go back.
Do you want to return to Khaddamari in the future?Yes
When do you think you are likely to return?Within the next month
What is the main reason that motivates you to return? Improved safety
What is the second most important reason? Missing home
What is the main issue which currently prevents return to Khaddamari? Food insecurity
What is the second most important issue preventing return? Financial cost of return
At no point in the interview did the respondent mention that he or she was likely to return in the next month. Food insecurity or financial costs were also not cited as factors preventing return. Without audio recordings, we would never have become aware of these issues. Transcribing even just a sample of our audio recordings drew attention to significant problems with the data. Instead of blindly relying on poor quality data, we were able to triangulate information from other sources, and use the interview transcripts as qualitative data. We also included a strongly worded limitations section in the report, acknowledging the data quality issues.
We suspect such data quality issues are common. Surveys, quite simply, are perhaps not the most appropriate tool for data collection in the contexts within which we operate. Certainly, there is a need to be more aware of, and more transparent about, survey limitations.
Despite these limitations, there is no doubt that surveys will continue to be widely used in the humanitarian community and beyond. Surveys are ingrained in the structure and processes of the humanitarian industry. Despite the challenges we faced in Nigeria, we will continue to use surveys ourselves. We know now, however, that audio recordings are invaluable for quality assurance purposes.
A manual audio recording strategy is difficult to replicate at scale
In an ideal world, all survey interviews would be recorded, transcribed, and translated. This would not only enhance quality assurance processes, but also complement survey data with rich qualitative narratives and quotes. Translating and transcribing recordings, however, requires a huge amount of technical and human resources.
From a technical standpoint, recording audio files of surveys is not straightforward. Common cell phone data collection tools, such as Kobo, do not offer full-length audio recordings as standard features within surveys. There are also storage issues, as audio files take up significant space on cell phones and stretch the limits of offline survey tools or browser caching. Audio recorders are easy to find and fairly reliable, but they require setting up a parallel workflow and a careful process of coding to ensure that each audio file is appropriately connected to the corresponding survey.
From a time standpoint, this process is slow and involved. As a general rule, it takes roughly six hours to transcribe one hour of audio content. In Hausa and Kanuri – two low resource languages that lack experienced translators – one hour of transcription often took closer to eight hours to complete. The Hausa or Kanuri transcripts then had to be translated into English, a process that took an additional 8 hours. Therefore, each 30-minute recorded survey required about one day of additional work in order to fully process. To put that into perspective, one person would have to work full time every day for close to a year to transcribe and translate a survey involving 350 people.
Language technology can offer some support
In languages such as English or French, solutions already exist to drastically speed up this process. Speech to text technologies – the same technologies used to send SMS messages by voice – have improved dramatically in recent years with the adoption of machine learning approaches. This makes it possible to transcribe and translate audio recordings in a matter of seconds, not days. The error rates of these automated tools are low, and in some cases are even close to rivaling human output. For humanitarians working in contexts with well resourced languages like Spanish, French, or even some dialects of Arabic, these language technologies are already able to offer significant support that makes an audio survey workflow more feasible.
For low-resource languages such as Hausa, Kanuri, Swahili, or Rohingya, these technologies do not exist or are too unreliable. That is because these languages lack the commercial viability to be priority languages for technology companies, and there is often insufficient data to train the machine translation technologies. In an attempt to close the digital language divide, Translators without Borders has recently rolled out an ambitious effort called Gamayun: the language equality initiative. This initiative is working to develop datasets and language technology in low-resource languages relevant to humanitarian and development contexts. The goal is to develop fit-for-purpose solutions that can help break down language barriers and make language solutions such as this more accessible and feasible. Still, this is a long term vision and many of the tools will take months or even years to develop fully.
In the meantime, there are four things you can do now to incorporate audio workflows into your data collection efforts
Record your surveys using tape recorders. It is a valuable process, even if you are limited in how you are able to use the recordings right now. In our experience, enumerators are less likely to intentionally skip entire questions or sections if they know they are being recorded. Work is underway to integrate audio workflows directly into Kobo and other surveying tools, but for now, a tape recorder is an accessible and affordable tool.
Transcribe and translate a small sample of your recordings. Even a handful of transcripts can prove to be useful verification and training tools. We recommend you complete the translations in the pilot stage of your survey, to give you time to adjust trainings or survey design if necessary. This can help to at least provide spot checks of enumerators that you are concerned about, or simply verify one key question, such as the question about informed consent.
Run your recordings through automated transcription and translation tools. This will only be possible if you are working in major languages such as Spanish or French. Technology is rapidly developing, and every month more languages become available and the quality of these technologies improve. Commercially available services are available through Microsoft, Google, and Amazon amongst others, but these services often have a cost, especially at scale.
Partner with TWB to improve technology for low-resource languages. TWB is actively looking for partners to pilot audio recording and transcription processes, to help gather voice and text data to build language technologies for low resource languages. TWB is also seeking partners interested in actively integrating these automated or semi-automated solutions into existing workflows. Get in touch if you are interested in partnering: [email protected]
Written by:
Chloe Sydney, Research Associate at IDMCEric DeLuca, Monitoring, Evaluation, and Learning Manager at Translators without Borders
If I had to summarize Translators without Borders’ learning from the Cyclone Idai response, it would be: language support can be a significant tool for effective, accountable humanitarian action. But only if there is a more comprehensive approach to community engagement from the outset.
It is one thing to read a statistic about the linguistic diversity and low literacy levels of the population in Mozambique. It is another thing entirely to sit down with a group of Cyclone Idai survivors in Beira and hear it in person. To learn from one person after another that they are unable to communicate with aid workers in a language they understand.
This is what TWB’s assessment team and I heard a few weeks ago when we conducted a rapid language assessment in four temporary accommodation sites. We found that many people do not understand the main languages and formats used by humanitarian organizations. They voiced frustration about how difficult it is to access information about available assistance. After one of southern Africa’s worst disasters in decades, we learned that much humanitarian communication is failing because it is in the wrong language.
Today, in the comfort of my home, I’m thinking about what this means. In a way, it shows that humanitarians still fall short of meeting their commitments to “leave no one behind” and “put people at the center.” This is probably not news to many. But it leaves me torn when thinking about the impact of TWB’s language support services in the Cyclone Idai response. Looking at our project, I can say we worked with others to strengthen communication with affected people in the relevant languages. But looking at the remaining gaps, I am less convinced that our work ensured effective engagement with all those affected from the onset of the response.
My point here is not to be skeptical about the first-phase emergency aid delivered in Mozambique. Many communities lost everything due to Cyclone Idai and rely on that aid to rebuild their lives. But I want to reflect on learning in the humanitarian sector. I think we generally try to question ourselves. However, it sometimes feels like we spend more energy evaluating how things went wrong after the fact than we do getting it right up front.
Credit: Andrew Lind / IOM
In recent years, there has been no shortage of research on the importance of meaningful community engagement. Effective two-way communication is an essential element of engagement. Yet, activities aimed at ensuring people’s voices are heard and understood are still implemented as optional ‘add-ons.’ They are rushed, under-resourced or restricted to the later stages of a response. That needs to change.
What then, can be done?
For a start, we need to collect and share language data as part of needs assessments. That data is a basis for workable and effective communication strategies. It tells organizations three key things:
Which language skills we need to recruit for;
Which languages and formats we need to provide information in; and
Which languages and communication preferences we need to tailor feedback mechanisms to.
Language assessments of the kind carried out by TWB in Beira can provide additional insight into information comprehension and specific vulnerabilities. On that basis, language support like translation and interpreting can be built into community engagement response plans and budgets.
It is not too late to start collecting, sharing, and using this data in the Cyclone Idai response. But we need to apply this change from the outset of the next emergency. It is the time to ensure we are accountable to the people that need it most, and that this process is in the languages and formats they want. We owe it to the people we aim to help – and to ourselves to maximize the learning we get from them.
Any takers?
Written by Mia Marzotto, Senior Advocacy Officer for Translators without Borders
Days in Beira, Mozambique are long and humid. The city and its surroundings are still reeling from the destruction caused by Cyclone Idai. Five weeks on, I see people seeking a sense of normality and routine: women and men walking on their way to work, children playing soccer on the street, families having barbecues on the weekend. Their resilience is astounding and yet the uncertainty about how to move forward makes the situation harder to cope with for many.
Credit: Andrew Lind / IOM
At one of the temporary accommodation sites in Beira, TWB’s assessment team and I met some of the people whose houses and livelihoods have been washed away. They patiently answered our survey, but they themselves had too many unanswered questions. Many were confused about the aid available; some had still no idea about the fate of loved ones; others wanted to go back but wondered what conditions were like where they came from.
Without the ability to get answers, I fear people might feel utterly abandoned. Without trusted sources of accurate, timely, and consistent information, rumors and misinformation can exacerbate the crisis. This can lead people to make poor decisions, or make them vulnerable to violence, extortion, and abuse.
The challenge is that people need the right information in the right language, right now. Nobody said it was easy, but if we are serious about our humanitarian commitments to effectiveness and accountability, it needs to be done.
That is why TWB is working with other humanitarian organizations to ensure a two-way conversation with affected people, especially the many that do not speak Portuguese. In the hardest hit provinces, the main local languages spoken and understood include Ndau, Nyanja, Lomwe, and Sena. One of our focuses has been mobilizing translators with the right language skills so that we can support making information available in local languages.
This is crucial work that is inspiring and humbling at the same time. Many of the translators we are working with have been directly impacted by Cyclone Idai. Gustavo, one of our volunteer translators, reminded me about this when we first met.
Gustavo is a high school teacher of English who has been translating critical information into and from Sena. Sitting at a desk in his classroom that still reeked of damp, he explained that people here are no strangers to natural disasters. Yet, a lack of information ahead of Cyclone Idai meant that few were prepared for its devastating impact. “The next day [after the cyclone] we could not recognize where we were. It was like there had been a war or a bomb which had destroyed everything: houses were gone; roads were cut; trees were down; there was no electricity or phone and internet connections,” he said.
Gustavo opened his home to host some of his neighbors and relatives who lost all their belongings. And when he received an email from TWB asking for his availability to help, he said “yes” right away. “I took the invitation as an opportunity to assist those in need with written or oral information in their own language. This is one of the best things I can do to help my community get back on its feet.”
A crisis like a cyclone, by its nature, is a traumatic event. But talking with Gustavo I am reminded about the powerful thing that is meaningful communication. Communicating with people about the situation and answering their questions can be critical. Helping people to understand where they can get help and how they can help themselves improves their psychological resilience and their ability to recover. Doing so in local languages is key to ensuring people understand information and can act on it to rebuild their lives.
There is no quick fix that will address all of people’s questions. However, I know that working with local translators is needed to come at the issue using the right languages. Together with our team, I intend to keep doing so.
As of 30 April, our team of volunteer translators has translated over 70,000 words into relevant local languages. Thanks to their support, we are filling information gaps on issues such as hygiene, health, shelter, safety, and preventing sexual exploitation and abuse. If you would like further information about our language support services in Mozambique, you can contact us at [email protected].
This project is funded by the H2H Fund, a funding mechanism for H2H Network members supported by UK aid from the UK government.
Written by Mia Marzotto, Senior Advocacy Officer for Translators without Borders
Translators improve lives by translating potentially lifesaving information into often ‘marginalized’ languages spoken by vulnerable individuals. Those who volunteer for Translators without Borders (TWB) have a range of experience and skills and share a vision of a world where knowledge knows no language barriers. We are grateful for all our translators, and we love sharing their stories.
Translation is not the only skill that helps TWB translators connect people through language. A deep understanding of culture, people, and precision can also help nonprofit organizations communicate with people affected by crisis or poverty.
“I am a translator to the marrow of my bones, and a perpetual learner — every translation for me is a discovery.” Liudmila Tomanek, Translator for TWB.
Take, for example, Russian translator Liudmila Tomanek. When she is not freelancing and running her translation company, this linguist with a penchant for perfection translates information for people in need, on a diverse range of topics. To date, she has donated over 225,000 words translated from English into her native Russian. Through her work with TWB, she uses and develops her communication skills and cultural understanding to help people understand vital information, no matter what language they speak.
Working in the real world
As a multilingual translator and interpreter working from English, French, Spanish, and Italian into Russian, Liudmila understandably has a range of experience and cultural knowledge. She draws on this in projects with TWB, and is comfortable working in diverse subject areas. Particular interests lie in journalism, economics, and medical translation.
During her time with TWB, Liudmila has used her deep cultural understanding to translate information on topics ranging from human rights to poverty and infectious diseases. In doing so, she has supported nonprofit organizations such as the American Red Cross, Internews, and the International Federation of Red Cross and Red Crescent Societies (IFRC).
Donating words
The very fact that TWB exists and flourishes, she believes, demonstrates that quality skills can be incredibly valuable when it comes to helping a good cause.
With her translated words, she reaches out to those who would otherwise lack the access to information they need in a language and format they understand. Liudmila compares her volunteering with TWB to doctors working for Doctors without Borders: professionals using their skills to treat people where the need is greatest. She explains, “professional translators who volunteer for TWB provide information where it is needed and in the language it is needed.” Projects with TWB have opened Liudmila’s eyes to the wide-ranging need for professional translation: from the families of children born with a cleft lip and palate, to natural disaster management.
It helps me to see the world through a different set of spectacles. It removes a curtain from some aspects of life that people prefer not to think or talk about. – Liudmila
Liudmila lists her projects with Operation Smile International among her favorites. “They really do amazing things. They go around the world and give children born with a cleft lip or palate a chance to smile and live a full life. I cry every time I translate their newsletter,” she says.
Befriending technology
And sometimes translating leads to new skills. As a self-confessed old-fashioned type, she was once wary of computer-assisted translation (CAT) tools. However, with Kató, TWB’s online translation platform, Liudmila was converted. Though a professional eye still is still needed to ensure context and quality, this translator now works faster and more consistently with Kató – and gladly so.
When helping the world communicate, we’re thankful that Liudmila uses skills both old and new.
Want to use your language skills for good? Applytoday.
Written by Danielle Moore, Communications Officer for Translators without Borders. Interview responses by Liudmila Tomanek, Translator for Translators without Borders.
This is what TWB’s assessment team and I heard a few weeks ago when we conducted a rapid language assessment in four temporary accommodation sites. 
