User:FLEM/Poems translations: Difference between revisions

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==.on the topic ==
==.on the topic ==


https://pamelaklein.wordpress.com/2012/07/12/translation-generator-poetry/ -->
https://pamelaklein.wordpress.com/2012/07/12/translation-generator-poetry/


https://lithub.com/what-we-can-learn-from-multiple-translations-of-the-same-poem/
https://lithub.com/what-we-can-learn-from-multiple-translations-of-the-same-poem/


https://www.npr.org/2018/04/15/602261007/-nprpoetry-literary-translator-aaron-coleman?t=1638394813534
https://www.npr.org/2018/04/15/602261007/-nprpoetry-literary-translator-aaron-coleman?t=1638394813534

Revision as of 16:03, 2 December 2021

.input

i recently received a new poetry book from the same author of a book that I've been carrying with me for a long time

one day, while reading my favourite poem, Fiesta, I started to play around with the two translations offered by both books

i did like that word, i did not like the structure of the sentence in the other translation, i wanted a different word for the end of that line

at the end i created a new translation based on the two originals and i started to question myself on this topic

how does a translator choose words?

why do they choose .a instead of .b? .c instead of .a?

not all translations are perfect so then, why not mix them up?

.the poem

.fiesta

The glasses were empty So the glasses were empty

The bottle was shattered and the bottle broken

The bed was wide open And the bed was wide open

The door was tight shuttered and the door closed

Each shard was a star And all of the glass stars

Of bliss and of beauty of happiness and beauty

That flashed on the floor were sparkling in the dust

All dusty and dirty of the poorly dusted room.

And I was dead drunk And I was dead drunk

Lit up wildly ablaze And I was a bonfire

You were drunk and alive And you were alive, drunk,

In a naked embrace! all naked in my arms.

.vernacular maps as a starting point

starting from the data received from the tool of the vernacular maps

comparing results and find out common words / differences but the content wasn't the right one to do this

made a function for common words

didn't know how to fit into the vernacular maps

.vernacular poem translations

by collecting translations made by people from different languages and compare them

.a choose a poem in english

.b provide different language translations

.c ask people to use the translation in their own language and to translate it to english

.d compare original translation with the new vernacular ones

// why not going back to vernacular maps and try out the new filter on that content? ANSWER FOUND

.vernacular translations maps

."seeing what different translators have done with the same poem immediately eliminates easy assumptions that beginning translators often make: that there is a single way, a most correct way, or a best way to translate a poem." ."We might begin by asking where, on a continuum ranging from the most “literal” to the most “free,” a particular translation lies. Where, on another continuum between most loyal to form and most free of it, does a translation of a formal poem lie? What is gained by attempting to replicate meter and/or rhyme, and what is lost? What about levels of diction? More generally, what is the stylistic “register” of a translation, ranging from formal to colloquial, or is there a mixture of styles?"° --> why not going back to vernacular maps with this? not even need the filter, the filter exists just to analyse material in a specific way. why not create vernacular maps from these vernacular translations? ask people to write on the image of the text their personal translation. what is the right way to translate a poem? then work on the content gathered and create new maps out of the texts

instructions: translate the following text to english in the way you feel, word by word, using negative space writing on the text off the text following the lines or not? //

.what

A function that:

1. takes into account 2 similar texts (example: 2 different translations of a poems)

2. finds the common words and uses them as the fixed text for the new piece of text

3. puts the results together into a new piece, randomly choosing the different options

4. html output that highlights the different random choices of the translations

.production process

.from my notebook 18.11.21

book translations

.a choose poems

.b take different translations

.c select sentences and words that are different

.d import random from choice (from the text's translation

.e highlight the word that's different

.f when you slide on it you can see the different options EXTRAJAVA

.from my notebook 26.11.21

text1 = " the glasses were broken "

text2 = " the glass is broken "

starting text = " the _____ ____ broken"

random choice between glasses were // glass is

random chosen poem translation

.a print differences

.b print equals

.c organise random choice scheme?

fixed_terms + choice(differences) // remove differences leaving a space reference --> replace?

! in a line, it should choose one version

could it be possible to highlight differences later? now use the whole sentence now

.from my notebook 29.11.21

.a go through the text --> find difference

e i bicchieri eran vuoti

ed i bicchieri erano vuoti

.b reposition with random choice

// tokenize words

should this be random choice with no meaning or actually putting the text back in order to show the real translations?

.from my notebook 30.11.21

gathering information from people reading poems out loud and producing transcriptions with the use of an automatic translator // compare them between different languages? with vernacular poems? with originals?

.not from my notebook 01.12.21

.seeing what different translators have done with the same poem immediately eliminates easy assumptions that beginning translators often make: that there is a single way, a most correct way, or a best way to translate a poem."

.We might begin by asking where, on a continuum ranging from the most “literal” to the most “free,” a particular translation lies. Where, on another continuum between most loyal to form and most free of it, does a translation of a formal poem lie? What is gained by attempting to replicate meter and/or rhyme, and what is lost? What about levels of diction? More generally, what is the stylistic “register” of a translation, ranging from formal to colloquial, or is there a mixture of styles?°

--> why not going back to vernacular maps with this? not even need the filter, the filter exists just to analyse material in a specific way. why not create vernacular maps from these vernacular translations? ask people to write on

the image of the text their personal translation. what is the right way to translate a poem? then work on the content gathered and create new maps out of the texts

instructions: translate the following text to english in the way you feel, word by word, using negative space writing on the text of the text following the lines or not? //

.output

.methodology

.a new text with highlighted differences

.b both texts alongside

.c new text from random choice

--> possibility to extract the resulting file (pdf, txt file, word?)

.content

.a fixed poem translation

.b vernacular translations (made by people) // print out all the different translations in all languages

.physical output

// framed prints of the processes showcased step by step, also with mistakes --> printed(results) in the Jupiter Lab

! do a session with people trying out the tool and print the results out

.possibilities

.why this is an enriching and fascinating tool

confronting texts in education to understand differences?

to understand the job of a translator?

to enrich the experience of reading a translated text?

.More specifically, multiple translations can give us a much better sense of the poem than a single translation can, so that even if we can’t read the poem in the original language, we can come closer to that experience. °

.on the topic

https://pamelaklein.wordpress.com/2012/07/12/translation-generator-poetry/

https://lithub.com/what-we-can-learn-from-multiple-translations-of-the-same-poem/

https://www.npr.org/2018/04/15/602261007/-nprpoetry-literary-translator-aaron-coleman?t=1638394813534