Agirrezabal1, Mans Hulden2, Bertol Arrieta1, Aitzol Astigarraga1 (1) Euskal Herriko Unibertsitatea / University of the Basque Country (UPV/EHU) (2)University of Helsinki July 15th, 2013 11th Conference on Finite-State Methods and Natural Language Processing St. Andrews, Scotland https://zeuscansion.googlecode.com 1/38
do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 3/38
2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 4/38
of polysyllabic words... contribute to the rhythm of the language. ...If the scansion of a line meant al l the phonetic fact, no two line would scan the same way... C.S.Lewis en.wikipedia.org Meter The elements that influence the meter are very limited. In the case of English poetry, meter is described as a sequence of feet (a grouping of syllables usually containing one stressed syllable). en.wikipedia.org 5/38
Metrical patterns 2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 9/38
Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 11/38
only. AnalysePoems (Plamondon, 2006): Identifies patterns, does not impose them. Rhymes also checked. Calliope (McAleese, 2007): Scandroid improvement using linguistic theories. 12/38
only. AnalysePoems (Plamondon, 2006): Identifies patterns, does not impose them. Rhymes also checked. Calliope (McAleese, 2007): Scandroid improvement using linguistic theories. (Greene et al., 2010): Statistical methods in the analysis. It uses WFST for stress assignment. 12/38
2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 13/38
call to me call to me Output: [’ - - ][ ’ - - ][’ - -][’ - -] Problem no1: we can’t just use a dictionary Woman much missed how you call to me call to me ’ - ’ ‘ ’ ’ ’ - ’ ’ - ’ 14/38
call to me call to me Output: [’ - - ][ ’ - - ][’ - -][’ - -] Problem no1: we can’t just use a dictionary Woman much missed how you call to me call to me ’ - ’ ‘ ’ ’ ’ - ’ ’ - ’ Problem no2: Divide stresses into feet Woman much missed how you call to me call to me [’ - - ][ ’ - - ][’ - -][’ - -] 14/38
call to me call to me Output: [’ - - ][ ’ - - ][’ - -][’ - -] Problem no1: we can’t just use a dictionary Woman much missed how you call to me call to me ’ - ’ ‘ ’ ’ ’ - ’ ’ - ’ Problem no2: Divide stresses into feet Woman much missed how you call to me call to me [’ - - ][ ’ - - ][’ - -][’ - -] Problem no3: There are some unknown words: Wanna brewsky? brewsky -> brisky 14/38
2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 16/38
I dwell in Possibility A fairer House than Prose More numerous of Windows Superior for Doors Of Chambers as the Cedars Impregnable of Eye And for an Everlasting Roof The Gambrels of the Sky Of Visitors the fairest For Occupation This The spreading wide my narrow Hands To gather Paradise 1 - / - \-/-- 2 - \- / - / 3 / /-- - \- 4 -/-- - \ 6 - \- - - \- 7 -/-- - / 8 - - - \-/- / 9 - \- - - / 11 - \-- - \- 12 - \-/- - 13 - \- / - /\ \ 14 - /- /-\ 17/38
2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 18/38
provide a reasonable stress asignment for scansion -Needs access to POS information 1 Stress the primarily stressed syllable in content words1 1such as names, verbs, adjectives and adverbs 22/38
provide a reasonable stress asignment for scansion -Needs access to POS information 1 Stress the primarily stressed syllable in content words1 2 Stress the secondarily stressed syllable of polysyllabic content words 1such as names, verbs, adjectives and adverbs 22/38
provide a reasonable stress asignment for scansion -Needs access to POS information 1 Stress the primarily stressed syllable in content words1 2 Stress the secondarily stressed syllable of polysyllabic content words and the most strongly stressed syllable of polysyllabic words. 1such as names, verbs, adjectives and adverbs 22/38
2nd Step CleanUp -------------------------------------------------------------------------------------- I I+PRP I+-+PRP I+-+PRP - dwell dwell+VBP dwell+’+VBP dwell+’+VBP ’ in in+IN in+-+IN in+-+IN - possibility possibility+NN possibility+--’--+NN possibility+‘-’--+NN ‘-’-- English poetry text T okenizer POS-tagger 1st step 2nd step RHYTHMI-METRICAL SCANSION GROVES' RULES Metrical information Are the words in the dictionary? Y Closest word finder N Cleanup 23/38
finds the closest spelled word in the dictionary. We need this because English is not a phonemic language We chumped and chawed the buttered toast Phantasmagoria and other poems, Lewis Carroll 24/38
finds the closest spelled word in the dictionary. We need this because English is not a phonemic language We chumped and chawed the buttered toast Phantasmagoria and other poems, Lewis Carroll chumped and chawed are not in the dictionary. 24/38
finds the closest spelled word in the dictionary. We need this because English is not a phonemic language We chumped and chawed the buttered toast Phantasmagoria and other poems, Lewis Carroll chumped and chawed are not in the dictionary. We must find a similarly pronounced word. 24/38
rules: 1 At the end of the word, higher cost (Word splitter) 2 We only allow a maximum of 2 character changes. 3 Character change order: 1 1 vowel 2 1 consonant 3 2 vowels 4 1 vowel and 1 consonant 5 2 consonants 25/38
rules: 1 At the end of the word, higher cost (Word splitter) 2 We only allow a maximum of 2 character changes. 3 Character change order: 1 1 vowel 2 1 consonant 3 2 vowels 4 1 vowel and 1 consonant 5 2 consonants Word splitter: chumped: chum|ped chawed: cha|wed 25/38
m p e d | c h a w e d | | | | | | | | | | | | | | - h u m p e d | c h e w e d The similarly pronounced words presented by the system are humped and chewed. 26/38
m p e d | c h a w e d | | | | | | | | | | | | | | - h u m p e d | c h e w e d The similarly pronounced words presented by the system are humped and chewed. we we+PRP we+-+PRP we+-+PRP - chumped chumped+VBD humped+‘+VBD humped+‘+VBD ‘ and and+CC and+-+CC and+-+CC - chawed chawed+VBD chewed+‘+VBD chewed+‘+VBD ‘ the the+DT the+-+DT the+-+DT - buttered buttered+JJ buttered+‘-+JJ buttered+‘-+JJ ‘- toast toast+NN toast+’+NN toast+’+NN ’ 26/38
Gitche Gumee, By the shining Big Sea Water, Stood the wigwam of Nokomis, Daughter of the Moon, Nokomis. Dark behind it rose the forest, Rose the black and gloomy pine trees, Rose the firs with cones upon them; Bright before’ it beat the water, Beat the clear and sunny water, Beat the shining Big Sea Water. The song of Hiawatha, Henry Wadsworth Longfellow - - ‘ - ‘ ? - - ‘ - ’ ’ ’ - ’ - ’ ‘ - ‘ - ’ - - - ’ ‘ - ’ - ‘ - ’ - ’ - ’ - ’ - ‘ - ’ ‘ ’ - ‘ - ‘ - ’ - ’ - ’ - ’ - ’ - ’ - ’ - ‘ - ’ - ’ - ‘ - ’ ’ ’ - 28/38
do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 30/38
759 scanned (by experts) poetry lines2 200 of them were correctly scanned by ZeuScansion (26.35 %) 2Some lines have several alternative scansions 32/38
759 scanned (by experts) poetry lines2 200 of them were correctly scanned by ZeuScansion (26.35 %) 7,076 syllables 2Some lines have several alternative scansions 32/38
759 scanned (by experts) poetry lines2 200 of them were correctly scanned by ZeuScansion (26.35 %) 7,076 syllables 6,002 of them were correctly scanned by ZeuScansion (84.82 %) 2Some lines have several alternative scansions 32/38
patterns 2 Scansion–why do we need it? 3 Related work 4 Scansion–why it’s difficult? 5 ZeuScansion: the output 6 ZeuScansion: technical details Groves’ rules Closest word finder Global analysis 7 Evaluation 8 Discussion & future directions 33/38
English poetry Phonetically closest word finder The evaluation results are promising FUTURE WORK: Do statistical inference about global metric pattern of the poem Improve closest word finder performance Replace HMM POS-tagger with a deterministic FST-based tagger (e.g. Brill’s tagger) 34/38
Agirrezabal1, Mans Hulden2, Bertol Arrieta1, Aitzol Astigarraga1 (1) Euskal Herriko Unibertsitatea / University of the Basque Country (UPV/EHU) (2)University of Helsinki July 15th, 2013 11th Conference on Finite-State Methods and Natural Language Processing St. Andrews, Scotland https://zeuscansion.googlecode.com 38/38