My Own Language (Final Project)

Performance Slides:

https://docs.google.com/presentation/d/e/2PACX-1vTUI1cbJfTLX_dZ8rv0qEeszYrbp6k5-FL9klGtwSCaS2sUKTrWkGuGkKzVZ3adlaE0FfRZ8JY-QZD6/pub?start=false&loop=false&delayms=3000

The concept:

I began this project by trying to find the intersection of (i) my tension with language and (ii) the unique properties of electronic text.

My tension with language:

• The difficulty in communicating my feelings with words
• The difficulty in describing and perceiving sensorial information with words (Sissel Tolaas, a scent artist and researcher, has the same theory and has invented a fictional language for smells in this ongoing project ’NASALO’, an alphabet for the nose. https://www.researchcatalogue.net/view/7344/7350)

The unique properties of electronic text:

• The ability to process large amounts of data:
  • look up pronunciation
  • look up similar words (word vectors)
  • predict texts
• The ability to randomise and produce unexpected outcomes

With this thought and with the interest of time and ability to collect a legitimate corpus, I decided to go with my first tension, ‘the difficulty in communicating my feelings with words’.

I often find myself talking to myself/my partner in My Own Language. At the beginning it sounded silly and gibberish to say it out loud, but because it is for the sake of emotional expression, it soon felt very expressive and satisfying to be able to channel out the emotions sonically.

However, there is still a great comparison between My Own Language and what I express to others outside of my relationship. This made me wonder if I could somehow lead people into My Own Language to understand what is going on internally.

The process:

1. I recorded myself talking in My Own Language during various emotional encounters and transcribed the recordings into text corpuses

   HUNST YUNST RUNST RAR TARAK NASAPASAK TAKST KRASK HASK HUSK TUSK MUSK HAFUSK PASUSK PARARUSK HAFARUSK PASUSK PASSUK PASSK HASSK PHASASSK HAMUSK HUSK YUCK YUK HUCK HUSK HAASK TAASCK PHASHASSCK HASA PASASSKA SAWASSKA HATAAKA PASIMAKA TUTCHKA PHALASKA RARKKKK PHASKKKK

2. I analysed the corpuses to find patterns and repetitions in the characters

   [(('P', 'A', 'S', 'A'), 17),
    ((' ', 'P', 'A', 'S'), 17),
    (('K', ' ', 'P', 'A'), 12),
    (('N', 'S', 'T', ' '), 12),
    (('U', 'N', 'S', 'T'), 11),
    (('A', 'K', 'U', 'K'), 11),
    (('K', 'U', 'K', ' '), 11),
    (('U', 'S', 'K', ' '), 11),
    (('K', ' ', 'H', 'A'), 10),
    (('A', 'T', 'A', 'K'), 10),]

3. I took the most common set of characters and translated those into pronunciation

   pasa = pronouncing.search("P AH0 S AH0")
   unst = pronouncing.search("AH0 N S T")
   atak = pronouncing.search("T AH1 K")
   akuk = pronouncing.search("K AH1 K")
   phas = pronouncing.search("F AH0 S")

4. I looked up words with the same pronunciation and manually excluded those which are too ‘far off’ from My Own Language
5. I compared those words with what I end up expressing

The raw output:

Panic

GKKKKK HUNST HAFATATATATATAK G SAH PHAAAAAAA HUNST PHASASSK PSHGK PASUSK SAFASHAFA PASA PASSK PHSAKUK REDIT KAPASHTATUK YUCK TANST MAWALAH FOSE


PASAHUNST PASATUK
KUNST HUNST
PASASHKAMAQAFASAMATAK NAFASHAPASATAK
PAKUK STAAKAKUK
PHASAKUK PHASASSK


UNSTABLE KUCK CONSTRAINED EMPHASIZED UNBALANCED CUCKOO STUCK CONFISCATED


FRUSTRATED STUCK PANIC


PANIC

Bubbly

YAHI RADIDIDOO BARINI WAROO SAAKALAHEE MI II WARAWI YIHAH BASHIBI HOOWASHASHASHOHI WAREE YAKINI PADI DADADIDOODI HAANY DEE SI BODABEE LAWRINI


SHASHI SHASHI
HASHIBII HASHI
PADEE RADEE
SHASHI SHASHI
SHAKADIDI RADIDO


BLOODY ADID WASHY SQUASHY MOTOHASHI MUDDY MUDDIED SHUSTER


BUBBLY HAPPY SMILEY


BUBBLY

Hollow

MAROON PHUL HAAZAR PARAUWA PHUL QUIET PUAW ROAM LAURAHAUW PASHEE ROME SAPHEYE TAZARA ZAHARAH WROOH NOO NOSSE WARAHARAU HAUWA FAAAAAAA


RARAH RAZARAH
PARAUW PARAUWA
RAZAPA RAZAR
HASSOON MOONSOON
HAAZAR SHAZAR


WOUNDED COCOON POSTOPERATIVE CITIZEN REPRESENTATIONAL PREOPERATIVE BRUUN REPRESENTATIONS


FRAGILE HOLLOW LOST


HOLLOW

 

The final layout:

• I decided to create a funnel-like aesthetic to illustrate the funnelling of my emotional experience to my actual expression
• I reorganised my original output which separates My Own Language with existing words to alternate the words in order to highlight the similarity in pronunciation (suggested by Allison)

To be improved / studied further:

• Instead of manually excluding words I can use the ‘added distance’ technique to exclude them
• The techniques in translating graphemes to phonemes
• Sound poetry (reference: http://rwet.decontextualize.com/schedule/)
  • Borroff, Marie. “Sound Symbolism as Drama in the Poetry of Robert Frost.” PMLA, vol. 107, no. 1, 1992, pp. 131–44. JSTOR, doi:10.2307/462806.
  • Bök, Christian. “When Cyborgs Versify.” The Sound of Poetry/The Poetry of Sound, edited by Craig Dworkin and Marjorie Perloff, University of Chicago Press, 2009, pp. 129–41.
  • Hinton, Leanne, et al. “Introduction: Sound-Symbolic Processes.” Sound Symbolism, Cambridge University Press, 1995. ProQuest Ebook Central,http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=4641097.
  • Hrushovski, Benjamin. “The Meaning of Sound Patterns in Poetry: An Interaction Theory.” Poetics Today, vol. 2, no. 1a, 1980, pp. 39–56. JSTOR, doi:10.2307/1772351.
  • Aji, Hélène. “Impossible Reversibilities: Jackson Mac Low.” The Sound of Poetry / The Poetry of Sound, University of Chicago Press, 2009, doi:10.7208/chicago/9780226657448.003.0013.
  • Perloff, Nancy. “Sound Poetry and the Musical Avant-Garde: A Musicologist’s Perspective.” The Sound of Poetry / The Poetry of Sound, University of Chicago Press, 2009, doi:10.7208/chicago/9780226657448.003.0009.

Last notes: 

In this project I hope to draw the readers / audience closer to my feelings, and in the long run I hope to create a piece which lies on the thin line of being gibberish and expressive – which has been a theme for all my work (blending the noise and the tangibles).

The corpuses, codes and presentation slides can be found here: https://github.com/hellonun/my-own-language