Saturday, March 13, 2021

Cathy Hirano: Translation is a door to another world - The Japan Times - Translation

Translator Cathy Hirano balances her time between freelance translations and young adult literature, and has earned accolades for both. Although her most recognized translations are for lifestyle guru Marie Kondo’s wildly popular works, starting with “The Life-Changing Magic of Tidying Up,” Hirano’s translations have also won awards in children’s literature.

While she was growing up in Canada, however, Hirano had no specific interest in Japan. It was her desire to take chances and go beyond her comfort zone that led her down a path she did not expect. After graduating from high school, she pursued a certificate in carpentry, hoping to get an apprenticeship.

“At that time, it was the beginning of a recession, so for a woman just starting out in a man’s field, I could see there wasn’t much future for me in Canada,” Hirano, 63, says. Although she had little interest in attending university, she had a passion for learning. “I really wanted to learn, and I thought the best way to do that would be to travel the world.”

When a serendipitous opportunity arose — a Japanese-Canadian former classmate was planning a trip to Japan and asked Hirano to accompany her — Hirano jumped at the chance. Even though her friend backed out at the last minute, Hirano went anyway, staying with her friend’s parents in Kyoto. It was 1978, and not the education she was expecting.

“Profoundly influenced as a teenager by the teachings of Bahaʼu’llah (a Persian religious leader who advocated universal peace), I had expected to see the oneness of humanity. Yet, when I got to Japan, it was a big shock to realize I held so many assumptions that were different from the Japanese surrounding me. Even the way a door opens — I would get up in the middle of the night and couldn’t open the door because I was trying to find a doorknob. But I gradually began to glimpse that oneness on a deeper level and it fascinated me.”

Her experiences inspired her to study cultural anthropology. A year after arriving in Japan, she enrolled at International Christian University in Mitaka, Tokyo. “It was two years of semi-intensive Japanese study first,” Hirano says. “ICU had a really innovative Japanese language program, and I had to learn Japanese so I could study cultural anthropology.”

During her studies, a friend from ICU found work at a publishing firm and asked Hirano to read children’s books in Japanese and provide English summaries for promotional use. Hirano loved it: Growing up as the granddaughter of a librarian, books were always in the house, and she welcomed the chance to receive free books of any kind.

Hirano went on to make translation her career, at first working in-house at a consulting engineering firm for three years. When she and her Japanese husband moved to the countryside in Kagawa Prefecture, Hirano started freelancing while raising their children. Although she translated everything from construction engineering texts to inspirational books, children’s and young adult literature continued to be her passion. Her translation of Kazumi Yumoto’s middle-grade novel “The Friends,” won the Boston Globe-Horn Book Award in 1997, and Nahoko Uehashi’s “The Beast Player” won a Michael L. Printz Honor in 2020.

Why do you translate?: “I want to share that experience of coming into another culture and learning to see through different eyes. We’re all looking at the same thing. But when you come into another culture and learn another language, you get to see it from a whole new perspective. It’s so mind-opening. That’s why I kept translating children’s books — I wanted kids to have that door to another world.”

Why young adult fiction?: “Some people write for kids and they have a set idea of who kids are. But the Japanese children’s writers I’ve been lucky to translate are writing for people. They’re writing stories that they want to read or exploring issues that they want to understand. These books speak directly to my heart. They allow me to see life in a new way.”

Advice for translators: “For me, translation tends to be fairly isolated work, so it’s easy to lose confidence in what I’m doing because it’s not possible to translate with exactness. You simply can’t get everything across. But every time, just do your very best because it’s better than if the work had never been translated. You’re the one being given this chance.”

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Guide to Google's Tensor2Tensor for Neural Machine Translation - Analytics India Magazine - Translation



Tensor2Tensor, shortly known as T2T, is a library of pre-configured deep learning models and datasets. The Google Brain team has developed it to do deep learning research faster and more accessible. It uses TensorFlow throughout and aims to improve performance and usability strongly. Models can be trained on any of the CPU, single GPU, multiple GPU and TPU either locally or in the cloud. Tensor2Tensor models need minimal or zero configuration or device-specific code. It provides support for well-acclaimed models and datasets across different media platforms such as images, videos, text and audio. However, Tensor2Tensor demonstrates outstanding performance in Neural Machine Translation (NMT) with a huge collection of pre-trained and pre-configured models and NMT datasets.

Neural Machine Translation has a long history and is still in progress with a variety of emerging approaches. Neural Machine Translation found its great success using the recurrent neural networks employed with LSTM cells. Since the input sequence to the recurrent neural network must be encoded to a fixed-length vector, it showed poor quality results in translating long sentences. This issue was partially overcome by models with ensemble or stack of gated convolutional networks and recurrent neural networks. Tensor2Tensor based Transformer architecture built with stacked self-attention layers becomes the new state-of-the-art model in Neural Machine Translation with drastically reduced training cost and remarkably improved BLEU score. This architecture has been introduced by Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Łukasz Kaiser, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit of Google Brain and Nal Kalchbrenner of DeepMind.

Unlike RNN models, Tensor2Tensor based Transformer has no fixed-sized bottleneck problem. Each time step in this architecture has direct access to the full history of the sequence of inputs enabled by the self-attention mechanism. Self-attention mechanism is known to be a powerful tool in modeling sequential data. It enables high speed training as well as maintaining distance-temporal relationships even during translation of long sequences. The transformer Neural Machine Translation model is composed of two parts: an encoder and a decoder. The encoder and decoder parts are built with stacks of multi-head self-attention layers and fully connected feed forward network layers. 

Tensor2Tensor
Tensor2Tensor Transformer Architecture

Methodology of Tensor2Tensor

Tensor2Tensor comprises five key components for the training run. They are:



  1. Datasets
  2. Device Configuration
  3. Hyperparameters
  4. Model
  5. Estimator and Experiment

Datasets are encapsulated into an input pipeline through the ‘Problem’ class. These classes are responsible for supply of preprocessed data for training and evaluation. Device configurations such as type of processor (CPU, GPU, TPU), number of devices, synchronization mode, and devices’ location are specified. Hyperparameters that instantiate the model and training procedure must be specified along with codes to be reproduced or shared. Model ties together the architecture, datasets, device configurations and hyperparameters to generate the necessary target by controlling losses, evaluation metrics and optimisation. Estimator and Experiment are the classes that handle training in loops, creating checkpoints, logging and enabling evaluation. With the predefined and established approach, Tensor2Tensor achieves greater performance in multiple media platforms.

Python Implementation

Tensor2Tensor is installed using the command

!pip install tensor2tensor

The Tensor2Tensor based Transformer can simply be called and run to perform Neural Machine Translation with predefined setup using the following commands. It can be noted that the code auto-configures itself based on the available configuration settings such as device type, the number of devices and so on. The following commands fetch the data, train and evaluate the transformer model, and test the model by translating a few text lines from a predefined file. It should be noted that training may take hours to days based on the user’s configuration.

 %%bash
 # See what problems, models, and hyperparameter sets are available.
 # You can easily swap between them (and add new ones).
 t2t-trainer --registry_help
 PROBLEM=translate_ende_wmt32k
 MODEL=transformer
 HPARAMS=transformer_base_single_gpu
 DATA_DIR=$HOME/t2t_data
 TMP_DIR=/tmp/t2t_datagen
 TRAIN_DIR=$HOME/t2t_train/$PROBLEM/$MODEL-$HPARAMS
 mkdir -p $DATA_DIR $TMP_DIR $TRAIN_DIR 

The following codes fetch the data from the English-to-German translation task the input data pipeline.

 %%bash
 # Generate data
 t2t-datagen \
   --data_dir=$DATA_DIR \
   --tmp_dir=$TMP_DIR \
   --problem=$PROBLEM 

The following codes let the model train on the defined dataset, evaluate internally.

 %%bash
 # Train
 # If you run out of memory, add --hparams='batch_size=1024'.
 t2t-trainer \
   --data_dir=$DATA_DIR \
   --problem=$PROBLEM \
   --model=$MODEL \
   --hparams_set=$HPARAMS \
   --output_dir=$TRAIN_DIR
 # Decode
 DECODE_FILE=$DATA_DIR/decode_this.txt
 echo "Hello world" >> $DECODE_FILE
 echo "Goodbye world" >> $DECODE_FILE
 echo -e 'Hallo Welt\nAuf Wiedersehen Welt' > ref-translation.de
 BEAM_SIZE=4
 ALPHA=0.6
 t2t-decoder \
   --data_dir=$DATA_DIR \
   --problem=$PROBLEM \
   --model=$MODEL \
   --hparams_set=$HPARAMS \
   --output_dir=$TRAIN_DIR \
   --decode_hparams="beam_size=$BEAM_SIZE,alpha=$ALPHA" \
   --decode_from_file=$DECODE_FILE \
   --decode_to_file=translation.en 

The following codes enable user to sample check the translation performance on an unseen text

See Also
 %%bash
 # See the translations
 cat translation.en 

Finally, BLUE score can be calculated to evaluate the model with global standards

 %%bash
 # Evaluate the BLEU score
 t2t-bleu --translation=translation.en --reference=ref-translation.de 

As an alternative to Colab, Tensor2Tensor models can be easily run on cloud based FloydHub workspaces as it is preinstalled with Tensor2Tensor, highly supporting configured on-the-go pre-trained models.

Performance evaluation of Tensor2Tensor Transformer

Tensor2Tensor based Transformer exhibits great performance in respect of syntactic and semantic considerations in Neural Machine Translation. It shows much greater computational efficiency compared to Recurrent Neural Networks with reduced computational time and memory. Tensor2Tensor enables interpretation of language models with self-attention by visualizing the attention distribution. This architecture is evaluated using WMT 2014 Translation task. 

On the WMT 2014 English-to-French translation task, the Tensor2Tensor based Transformer model achieves a state-of-the-art BLEU score of 41.8, outperforming all of the previously published single models, at less than 1/4 the training cost of the previous state-of-the-art model.

On the WMT 2014 English-to-German translation task, the Tensor2Tensor based Transformer model achieves a state-of-the-art BLEU score of 28.4, outperforming all of the previously published single models and ensembles, at a fraction of the training cost of the previous state-of-the-art model. 

Further reading:


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Translation is the deepest kind of reading: Kazim Al.. with Ananda Devis poetry, relationship with languages - Firstpost - Translation

'Devi's poems seem simple — just like something that would be said between friends — but they turn and twist within, move strangely, maybe even 'darkly.''

Kazim Ali is a prolific author whose body of work encompasses multiple genres – poetry, fiction, prose and translation. His latest book to be published in India — When the Night Agrees to Speak to Me (Harper Perennial, 2021) — is an English translation of Ananda Devi’s Quand la nuit consent à me parler. It was originally written in French as a collection of poems with three short prose pieces at the end.

Devi, who was born in Mauritius, and traces her roots to India, is considered to be one of the most important Francophone writers in the world. She is fluent in French, Mauritian Creole and English, understands Hindi and German, and has lost Telugu – the language that her mother spoke to her in. Ali was born in the United Kingdom, and has lived transnationally in the United States, Canada, India, France and the Middle East.

Ali picked up a copy of Devi’s book in a Parisian bookstore en route to India, and began reading it in Pondicherry – which was once under French colonial rule. The book seized his attention in a way that made him start translating the work to arrive at a deeper reading. In this exclusive interview over email, Ali – who is currently a Professor of Literature at University of California, San Diego – speaks at length about the craft of translation.

How would you describe the poetry of Ananda Devi to someone who has never encountered it before, either in French or in translation?

These poems seem simple — just like something that would be said between friends — but they turn and twist within, move strangely, maybe even "darkly." For sure, anger and resentment flare in these poems, emotions we do not normally express.

What kind of impact do her words have on you?

In French, though there is great pain in these short lyrics, there is a fluidity in language too, a "beauty" in the way the phrases flow and turn; translating them into English necessarily brought out a thornier affect — it had to: the sonic qualities of the language are different, the grammatical structure of English blockier and less "connective" and supple than many-joined French. It's a less subtle language in fact, deep in its syntactical bones.

Why did you commit to translating her poems into English?

It happened without me thinking. I was reading in French, but my French is self-taught; I was never formally educated. So, there were many places I didn't know a word, or occasionally a grammatical construction. But rather than pick up a dictionary at every point I just continued reading to glean what I could. At some point, I understood a poem as a poem itself even if there were words in it that I didn't know. I think it is when I started looking at the prose pieces that close the collection that I really thought I wanted to render the poems in English as a way of reading them more deeply. I did not expect the transformative quality they had on me.

Would you mind sharing how you learnt French, and the place it has in your life now?

I learnt it informally. One of my uncles was a French major (at the English and Foreign Languages University in Hyderabad) and moved to Paris after his graduation to work for a French company. He met his wife there and has lived there ever since. One of my cousins is a poet and English teacher, and we have stayed in touch throughout his life. I went to see him in Paris, and though he spoke English, I always wanted to speak to him in his own native language. I learnt by spending time with my family and with my cousin and his friends, and by reading French writers I loved, especially Marguerite Duras. French (like other colonial languages) is no longer a European language. It is a South Asian language, a Vietnamese language, and African language, a Caribbean language. The literatures of all these places belong both the Francophone world but also to a global literary tradition.

In what way did the sights and sounds of Pondicherry and Varkala enter your translations?

Well, I wasn't in Pondicherry long, just an afternoon, but it's there that I started the work. It was really Varkala — on a cliff overlooking the Arabian Sea — that I started to imagine the landscape of Mauritius. Ironically (I suppose) the landscape itself doesn't appear much in the poems; they're smaller, take place in intimate and domestic spaces for the most part. But it was somehow the vibe of the place, the aura, the atmosphere, whatever you want to call it. I had to enter into a perceptual sense, and it was there that that happened for me.

Which aspects of Ananda Devi’s work seemed most difficult to translate?

I think in general the feel of the French language is really impossible to duplicate in English sonically. There may be languages that have some prosodic concordance with one another, some closer in general rhythm: for example, English and Dutch might be a little closer or even English and Danish than English and German. As far as French goes, sonically and rhythmically, it might be closer to Italian or Portuguese than it would be (for example) to Spanish, which has certain sonic affinities to Greek.

How did her complex relationship with various languages mirror your own multilinguality?

That made it easier actually. Devi writes in French by choice. She could as easily write in English or Creole, but the decision to write in French is both an aesthetic decision but a cultural one as well. I spoke many languages as a preliterate young child but lived and learned to read and write in only one. I think my brain was changed by my early polyphonic language acquisition and even though I mostly still live in English, it still feels like a foreign country, one I've only lately arrived in.

Translation is the deepest kind of reading Kazim Ali on working with Ananda Devis poetry relationship with languages

Cover image for When the Night Agrees to Speak to Me

In your Translator’s Note in the book, you say, “It was less karaoke and more full-blown drag.” Could you please help us unpack that statement? It seems that you are speaking as a translator, and as a queer poet fluent in the meanings and histories of drag.

It wasn't enough to just transmit the words, create a new version of those poems. I actually had to become Devi in a sense, I had to rewrite those poems as English poems. I was the poet who wrote those poems. I know they're not mine, I know that they're still hers, but there was something more — past "performance," closer to actual transformation that needed to take place within the body of the poem himself (myself) in order to write the English versions. And I wasn't just translating across languages, I was also translating across gender, and translating across age — they are the poems of an older woman, writing after a whole lifetime of experiences, which at the time (I did most of the initial work in 2012, though I finished somewhat after) I had not yet had.

How did your translations benefit from the comments you received from Ananda Devi?

She did read the translations and offered some feedback in the draft stage, but her comments were mostly in the area of clarifications. There were some very locally specific expressions I hadn't caught and at least one place where I had leaned into a colloquial meaning that she had not intended. But mostly — as she says in the interview we did that's included in the book — her interest is in writing her work; she does not translate it anymore (she did one of her own books in the past). She says it feels too much like rewriting a book, so she left me on my own. There was a panel we did later, at Oberlin College, where I was teaching, in which she expressed approval of the translations I'd done, even in a particular poem where I'd diverged not from her meaning but from the sound and rhythm, which one cannot properly duplicate in English. That meant a lot to me.

What points of convergence and conflict did you find between your own politics and hers?

I know friends who have translated work by poets with dramatically different political outlooks than they have, for example a friend in Israel who has translated the poetry of a very Zionist poet, a poet whose politics on the West Bank settlements are very different from her own, whose own literary community questioned why she was giving a platform to a poet she disagreed with politically. But thankfully, Ananda and I did not have such a divergence in political viewpoints.

To what extent did Ananda Devi's biographical details inform your appreciation of her poetry?

I didn't know much about them when I began, though I later came to understand more, particularly through her memoir Les hommes qui me parlent (The Men Who Talk to Me). Certainly, the more I learned about Mauritius and about Ananda's work, the better I was able to understand some of the themes and ideas in the poem. Some of the themes, like domestic violence, and the problem of child soldiers, she explores in different ways in novels like Le sari vert and La vie de Joséphin le fou (both as yet untranslated) and Le jours vivant (translated as The Living Days).

When you look back at your translations of Marguerite Duras, Sohrab Sepehri and Ananda Devi, what do you notice about your process as a translator?

In each case, it was falling in love with the work itself on its own terms, as literature in the other language. In both Duras' and Sepehri's case I read the work first in translation. The main — though not only — Duras translations I read were by Barbara Bray and Bray kind of created a Duras in English influenced (in my opinion) by Beckett's prose. It's a certain kind of Duras, not precisely the same as her French, but nonetheless a very distinctive voice in prose.

Sepehri I had only read a fairly weak translation of — his entire outlook as a poet is so embedded in Farsi literary traditions that it was nearly convoluted in English. I loved the images and the outlook, but it was beautiful as poetry in English, and so I viewed it as a kind of challenge. I don't read Farsi in fact, and so I teamed up with an Iranian scholar Jafar Mahallati and we did the work together, huddled over tables in coffee shops. He has the command of language that a poet would have, so it was very much a collaboration and I learned as much from him as I did from Sepehri. The work did not shed its complexity and there were times we'd spend a whole hour-long session on what a poem meant before we could even get to rendering it properly.

Whose work are you translating now/next?

I'm on a little pause from translation, though I have some coming out of Ivoirian poets; I did them a while ago though. I've also started studying Urdu during the pandemic and associated lockdown, so I've been working on Faiz Ahmed Faiz with my tutor. And some years ago, I did a few poems by Ahmed Faraz.

What has helped you hone your craft as a translator, and what advice would you offer translators who are starting out on their journeys?

I'd say study not only the language but also the culture, history, and literary traditions that produced the text you are trying to translate. If other translations exist of the author you are translating, I would suggest to read them, but read them and then put them aside; don't study them or engage too deeply. Translating is fun and it is also a great way of learning both language and about the text itself. I learnt more about Sepehri and Duras and Devi as well by translating them than I ever could have merely reading them. Perhaps what I mean is that translation is the deepest kind of reading.

How do you feel when you run into something that seems untranslatable?

Sometimes rather than "translate" it you have to rewrite it in the new language. It's a different poem in English, a new poem, but it draws from the same source, the same unspeakable experience that the "original" poem drew from. Walter Benjamin talks about this (in his essay The Task of the Translator) and I believe it: all poems, whether "original" or "translation" are attempts to translate the untranslatable, which is life itself, experience itself.

Chintan Girish Modi is a writer, educator and researcher who tweets @chintan_connect

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Friday, March 12, 2021

Skill Data Dictionary, Part 2: Taxonomies, Ontologies, and More - ATD - Dictionary

In our last blog post, we explained the key terminology around skill data and offered some definitions to help you understand and use them in your organization. This blog post will expand beyond the basics into the different methods of structuring your organization’s skill data.

There are many overlapping (or even contradictory) ideas about what it means to have a skill strategy and how that strategy relates to a skill taxonomy or ontology. These ideas aren’t inherently simple, but they don’t need to be overly complicated. That’s why we’re breaking them all down for you here.

Skill Strategy

Definition: A strategy for talent development that prioritizes skills as a way to measure the ability of your people. This measurement is aligned with the work that your organization needs to complete and the career opportunities that exist internally. Skill strategies can vary greatly between companies and can use any combination of upskilling technology, skill taxonomies, skill ontologies, skill clouds, or none of those.

Why It Matters: Using a skill strategy as opposed to a competency model (or in tandem with one) can help make your workforce more agile and enable opportunities for internal mobility and career growth.

Skill Taxonomy

Definition: A hierarchical system of classification that can categorize and organize skills in groups or “skill clusters.” A skill taxonomy is structured and will usually include the skills that are most important to business goals, sometimes with the skills’ definitions as well.

Why It Matters: This can help workers understand which skills they have from the taxonomy, how those skills relate to organizational needs, and what they should learn next. The purpose of the framework is not to capture every skill but to capture information about the most essential skills relevant to your business strategy.

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Skill Ontology

Definition: A set of skills and their relationships between one another.

Why It Matters: A skill ontology allows organizations to define and measure relationships between skills (and even jobs and people). It helps create a common language and understanding of skills across various different dimensions or platforms. Another way of looking at an ontology is that it is a “smart system” that helps maintain, aggregate, and simplify the skill data within a taxonomy.

Skill Graph

Definition: A skill graph shows the relationships between other skills and determines how skills map to roles, content, and other skill-related features. It’s often simply a visual representation of a skills ontology.

Why It Matters: Understanding how different skills are related to one another (and how closely they are related) can inform how artificial intelligence and models offer upskilling and mobility opportunities.

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Skill Cloud (Also Called a Skill Inventory or Skill Registry)

Definition: An inventory of skills across organizations that includes all known skill terms. It is the data set that is used to evaluate skills to include in organizational skill lists, ontologies, or taxonomies. It is basically a single source of truth for any skill, but it does not order or categorize skills like a taxonomy does.

Why It Matters: A skills cloud helps organize and standardize skills across an organization, but it alone does not make these skills actionable. They simply sit in the cloud.

Skills I/O

Definition: A skills I/O manages skills, skill data, and the structures mentioned above. You can use the skills I/O to build taxonomies, manage multiple skill sources, integrate different taxonomies, and edit the skills in your organization.

Why It Matters: Whereas taxonomies, ontologies, and graphs help us understand skills in relation to our business objectives, a skills I/O puts those concepts into practice together.

For more information on skill data, download The Ultimate Skill Data Handbook.

Women's Conference Funds $1 Million Bible Translation in 5 Hours | News & Reporting - ChristianityToday.com - Translation

The Bible translation alliance IllumiNations has a goal of making God’s Word accessible to all people by 2033, and it’s inviting partners to support its work one verse at a time.

Through IllumiNations’ 12 Verse Challenge (12VC), donors can cover translation costs for 12 verses of Scripture at $35 a month for a year. The challenge kicked off at this month’s virtual women’s conference IF: Gathering, where attendees pledged over $1.5 million toward the effort— enough to sponsor translating the entire Bible for an unreached people group and make significant progress on a second one.

As thousands of women tuned into the March 6 event, the display on the 12VC site scrolled through the chapters and verses their pledges had sponsored. More than 750 views signed up for the challenge within the first five minutes.

“We’re going to be Christians that know this book, love this book, believe this book, and give this book away,” said IF: Gathering founder Jennie Allen.

Allen watched alongside pastor David Platt, a speaker at the event, as the campaign met the cost of its first full Bible translation—just over $1 million—in a span of five hours, and the donations kept rolling in. “This is our most important work to date,” she said.

Translators estimate that nearly 1 billion people have little or no access to Scripture in a language they can understand (they call it “Bible poverty”).

IllumiNations, a collaboration among 10 top translating ministries, has been able to accelerate the timeline for all people to have access to the Bible from 2150 to 2033—as long as the funding comes through to back the translators already in the field. IllumiNations currently tallies 307 current projects on their website, each with a bar indicating how much more money is needed to complete the translation.

The translation funded by IF through the 12 Verse Challenge will go to people in western Ethiopia. “Because of you, we're able to help the Konta, Oyda, and Melo people groups of Ethiopia have the Bible in their language,” IllumiNations wrote in an Instagram post.

According to the Joshua Project, a combined 235,000 people speak Oyda, Melo, and Konta. Though Christianity is considered their primary religion, and they all have portions of the New Testament, none of these groups has a full Old Testament translation.

Allen said the funds raised will also help a translation project in a restricted country where churches must meet in secret. As of March 12, more than 6,300 women had pledged.

The IF fundraising campaign is the launch of the new 12 Verse Challenge model, and churches can now sign up to host a challenge themselves. IllumiNations says, “If just one percent of the Christians in America alone would fund the translation of 12 verses at $35 per verse, this task would be completed.”

This isn’t the first time IF: Gathering has highlighted Bible translation. The 2017 the event featured a Seed Company translator, and 650 women committed to monthly sponsorships to fund verse-by-verse translation.

Framing unreached people groups as living in Bible poverty makes the broad challenge of Bible access seem tangible and personal, like sponsoring a child in poverty. And during a time when many ministry connections have gone digital, it allows women participate in global missions without having to leave their ZIP codes.

Incremental faithfulness leading to global impact is baked into the DNA of IF: Gathering, founded in 2014. Its website says that if 4,000 women each disciple two women each year, and those two women then disciple two more each year, the chain reaction will lead to 4 million women discipled in a decade.

Historically, Christian women have been a driving force in Bible translation work. “If it hadn’t been for single women over the 70-year history of Wycliffe, half of the translations wouldn’t have been completed,” Russ Hersman, Wycliff Bible Translators’ former chief operations officer, told Christianity Today in 2017. At the time, women made up 85 percent of Wycliffe’s translation force.

“I cannot imagine a more powerful force on earth than these women in their places coming together to change things,” Allen said. “They are a tremendous force for good and change.”

The English Translation of Selena Gomez's Song "Buscando Amor" Will Surprise You - Seventeen.com - Translation

2020 hollywood beauty awards

Tibrina HobsonGetty Images

Selena Gomez's first Spanish-language EP, Revelación, is *finally* here and let's just say... I can't stop dancing.

This isn't the first time the "Lose You to Love Me" singer pays homage to her Mexican heritage — she's covered Tejana singer Selena Quintanilla's "Bidi Bidi Bom Bom" in the past, as well as feature on the 2018 smash hit "Taki Taki" alongside DJ Snake, Cardi B and Ozuna. She also dropped the single "Baila Conmigo" just last month.

Finally, Revelación is here and it’s Selena’s first full-length project entirely in Spanish.

During an Instagram Live, Selena said that "Buscando Amor," which translates to "Looking for Love" in English, is one of her fave songs on her new project. So, let's dive into these lyrics and see why.

This content is imported from YouTube. You may be able to find the same content in another format, or you may be able to find more information, at their web site.

[Intro]
They go out so they can see her
They get lost in the rhythm
They aren't looking for love
They aren't looking for love

Based on the title alone, some people would probably expect the second track on Revelación to be a slow jam or ballad about looking for a lover, but it is quite the opposite. Selena sings about what it's like to be single and have fun without the pressure of looking for love.

[Verse 1]
Let the rhythm take you over
That's how I like it, just like that
There's more to do tonight, I don't limit myself
The music is good and I don't resist

[Chorus]
They go out so they can see her because she likes to dance
They get lost in the rhythm, they start to forget
They aren't looking for anything, they're happy just as they are
Don't talk to her about love, that's not going to fly
They go out so they can see her because she likes to dance
They get lost in the rhythm, they start to forget
They aren't looking for anything, they're happy just as they are
Don't talk to her about love, that's not going to fly

"I’m actually grateful that I’m not involved with anyone right now," Selena said in an interview with the Los Angeles Times.

"Buscando Amor" is a reggaetón-infused bop that explores the idea of being content with yourself as you are. In the chorus, Selena sings "No están buscando na', 'tan bien así como están," which translates to "They aren't looking for anything, they're happy just as they are."

[Verse 2]
Today we're going out incognito
We're going to get into trouble
We're just partying, baby, we aren't looking for rings
When they play the music we go hard
Who doesn't like a Latina dancing to reggaetón?
Come if you want to taste it, leave if you're going to fall in love

[Bridge]
We won't stop until dawn
The party is over if we go
With our phones off

"We aren't looking for rings" further describes the idea of letting loose and having fun without the pressure of commitment. Things heat up in the second verse as Selena flirtatiously sings "Vente si quieres probar, vete si te vas a enamorar," which translates to "Come if you want to taste it, leave if you're going to fall in love."

In the bridge, she nods to partying with no phones and being present in the moment. In an interview with Kelly Ripa and Ryan Seacrest in 2019, Selena said that she deleted Instagram from her phone although she is one of the most-followed people on the app.

[Chorus]

They go out so they can see her because she likes to dance
They get lost in the rhythm, they start to forget
They aren't looking for anything, they're happy just as they are
Don't talk to her about love, that's not going to fly
They go out so they can see her because she likes to dance
They get lost in the rhythm, they start to forget
They aren't looking for anything, they're happy just as they are
Don't talk to her about love, that's not going to fly

[Outro]
They go out so they can see her
They get lost in the rhythm
They aren't looking for love
Leave if you're going to fall in love (They aren't looking)
Leave if you're going to fall in love

I seriously can't stop listening to "Buscando Amor," and I can't wait to listen to the rest of Revelación in all of its glory.

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Translation, personal contact underpin efforts to get COVID-19 vaccine to Durham's immigrant communities - WRAL.com - Translation

— Groups in Durham are taking the effort to spread awareness and access to COVID-19 vaccine to the streets.

It is a literal door-to-door project for Siembra NC. On Friday, the group was handing out information and answering questions for the residents of a primarily Hispanic neighborhood.

In the Bull City, about 14% of the population is Hispanic, but only about 5% of the first doses given in the city have been to Hispanic people.

A Siembra NC survey shows that, while 65.7% of those who responded are interested in getting a COVID-19 vaccine, 73.6% did not know how to go about it. So the group decided to meet people where they are – at home – to deliver that message.

"We want to protect our communities, so we are going to go door by door, neighborhood by neighborhood," said Siembra NC organizer Laura Garduño.

The group is asking to help to get that message into more homes.

"We know that there have been a lot of phone calls received on these local hotlines. But we know that the services aren’t always available in Spanish," Garduño said. Siembra NC is asking that the county provide a dedicated hotline for Spanish speakers to get vaccine information and appointments. "Websites should also be available in Spanish," she said.

Durham City Councilman Javiera Caballero joined Friday's door-to-door effort.

"If we actually want to meet this goal that President Biden set out for everyone that everyone over 18 by May should be able to get vaccinated, we’re not going to reach that goal if we don’t do some serious work in the community. I think we’re going to have to put in some serious effort and work if we are going to make the impact that we need to make," she said.

Thao Nguyen, policy lead at Greenlight Durham and a Duke University medical student, said the need goes beyond Spanish.

"We have a large Mandarin speaking population, for example. It’s really difficult for them to receive services because of language."

Nguyen said her own mother is among those who doesn't speak English or Spanish. She had to schedule her mother's appointment and accompany her to translate.

There are resources available, but not all realize they can access them.

"We have folks at Duke, medical students, who will help with these phone calls in Mandarin, help schedule the appointments and at the appointment times, help with interpretation if they need that as well," Nguyen said.

Greenlight and Siembra are partnering with GoDurham to make transportation available to those who need it and are pushing for vaccine clinics in communities where the need is greatest.

"We know that there are certain apartment complexes in Durham that have higher immigrant populations," Caballero said.

"We need to take it right to their doorsteps, because there are just so many barriers in asking them to come to Duke or the health department for example," Nguyen said.

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