Featured Linguist!

Jost Gippert: Our Featured Linguist!

"Buenos dias", "buenas noches" -- this was the first words in a foreign language I heard in my life, as a three-year old boy growing up in developing post-war Western Germany, where the first gastarbeiters had arrived from Spain. Fascinated by the strange sounds, I tried to get to know some more languages, the only opportunity being TV courses of English and French -- there was no foreign language education for pre-teen school children in Germany yet in those days. Read more

Donate Now | Visit the Fund Drive Homepage

Amount Raised:


Still Needed:


Can anyone overtake Syntax in the Subfield Challenge ?

Grad School Challenge Leader: University of Washington

Publishing Partner: Cambridge University Press CUP Extra Publisher Login

Discussion Details

Title: Automatical Metrical Markup
Submitter: Klemens Bobenhausen
Description: All,

automatic metrical markup (AMM) of written (not spoken) poetry means to
reach a 100% computer based analysis of the metrical information of a poem,
beginning with identifying poems (not yet reached), strophes, verse lines,
words, syllables and ending with distinction of pronounced (+) and
unpronounced (-) syllables and rhyme-schemata and putting all these
analysis in an XML-document (TEI P5 compatible).

Strophe 1:
(Fried|lich) (be|käm|pfen)
(Nacht) (sich) (und) (Tag) .
(Wie) (das) (zu) (däm|pfen) ,
(Wie) (das) (zu) (lö|sen) (ver|mag) !
Silben=5, Betonung=''+--+-''
Silben=4, Betonung=''+--+''
Silben=5, Betonung=''+--+-''
Silben=7, Betonung=''+--+--+''
Endreim=''abab'' (Kreuzreim)

After I collected lots of prosodic forecasts of the German written
language, I’m now able to analyse regular poems (with a regular row of
pronounced and unpronounced syllables for each verse/strophe) in about 100%
– and irregular poems (with an irregular row of pronounced and unpronounced
syllables for each verse/strophe) in about 98% of their syllables. The
amount of percents is a set of syllables

a) defined over pronounced syllables (60%)
b) defined over euphonic rules (25%)
c) defined over analogies to other verses (7%)
d) defined over unpronounced syllables (5%)
e) defined over rhymes (1%)

I’m not using any kind of POS or morphological tagging, because the system
should work also with historical texts and their orthography. The missing
2% are coming from foreign or non-Germanic words (like 'Musik' or 'Natur')
and compounds, which in German language are mostly pronounced on the part
of the compound which describes the other part (like 'Biergarten', being
pronounced on the first syllable, because 'Bier' describes which kind of
'Garten' a 'Biergarten' is.)

And now I’m out of ideas and need assistance. Is anyone interested in stuff
like this? The algorithm will not work with other languages than German,
but the ideas may.

Klemens (+-)
Date Posted: 04-Feb-2008
Linguistic Field(s): Computational Linguistics
Text/Corpus Linguistics
Ling & Literature
LL Issue: 19.410
Posted: 04-Feb-2008

Search Again

Back to Discussions Index