@InProceedings{Meyer-Sickendiek2018_407,
author = {Burkhard Meyer-Sickendiek and Hussein Hussein and Timo Baumann},
booktitle = {Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2018},
title = {Recognizing Modern Sound Poetry with LSTM Networks},
year = {2018},
editor = {André Berton and Udo Haiber and Wolfgang Minker},
month = mar,
pages = {192--199},
publisher = {TUDpress, Dresden},
abstract = {Our paper focuses on the computational analysis of “readout poetry”
(german: Hördichtung) – recordings of poets reading their own work – with regards
to the most important type of this genre, the modern “sound poetry” (german:
Lautdichtung). Whereas “readout poetry” often uses normal words and sentences,
the “sound poetry”, developed by dadaistic poets like Hugo Ball and Kurt Schwitters
or concrete poets like Ernst Jandl, Oskar Pastior, or Bob Cobbing, combines
the “microparticles of the human voice” like the segments in Ernst Jandls sound
poem “schtzngrmm” (“schtzngrmm / schtzngrmm / tttt / tttt / grrrmmmmm / tttt
/ sch / tzngrmm”). Within the genre of sound poetry, there are two main forms:
The lettristic and the syllabic decomposition. A short anecdote will explain this
difference: The dadaist Raoul Hausmann developed the lettristic sound poetry in
his early dadaistic poem “fmsbw” from 1918. This is said to have inspired his successor
Schwitters, whose famous “Ursonate” [The Sonata in Primal Speech] begins
with the words “Fümms bö wö tää zää Uu”. With the “Ursonate”, Schwitters developed
a syllabic variation of the lettristic poems of Hausmann. The paper shows how
to train a bidirectional LSTM network in order to differ between these “dadaistic”
sound poems and the “normal” read out poems. In a further step, we will also show
how to distinguish between the lettristic and the syllabic decomposition. Based on
a bidirectional LSTM network that reads encodings of the character sequence in
the poem and uses the output of each directional layer, we identify poems of the
sound poetry genre and differentiate between its two types of decompositions. The
classification results of sound poetry vs. other poetry as well as lettristic vs. syllabic
decomposition are with a high performance, yielding a f-scores of 0.86 and 0.84,
respectively.},
isbn = {978-3-959081-28-3},
issn = {0940-6832},
keywords = {Speech Processing and Prosody},
url = {https://www.essv.de/pdf/2018_192_199.pdf},
}