@inproceedings{BaumannHusseinMeyerSickendieketal., author = {Baumann, Timo and Hussein, Hussein and Meyer-Sickendiek, Burkhard and Elbeshausen, Jasper}, title = {A Tool for Human-in-the-Loop Analysis and Exploration of (not only) Prosodic Classifications for Post-modern Poetry}, series = {Informatik 2019 : 50 Jahre Gesellschaft f{\"u}r Informatik Workshop-Beitr{\"a}ge Fachtagung vom 23.-26. September 2019 in Kassel}, booktitle = {Informatik 2019 : 50 Jahre Gesellschaft f{\"u}r Informatik Workshop-Beitr{\"a}ge Fachtagung vom 23.-26. September 2019 in Kassel}, editor = {Draude, Claude and Lange, Martin and Sick, Bernhard}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, isbn = {978-3-88579-689-3}, pages = {151 -- 156}, abstract = {Data-based analyses are becoming more and more common in the Digital Humanities and tools are needed that focus human efforts on the most interesting and important aspects of exploration, analysis and annotation by using active machine learning techniques. We present our ongoing work on a tool that supports classification tasks for spoken documents (in our case: read-out post-modern poetry) using a neural networks-based classification backend and a web-based exploration and classification environment.}, language = {en} } @inproceedings{HusseinMeyerSickendiekBaumann, author = {Hussein, Hussein and Meyer-Sickendiek, Burkhard and Baumann, Timo}, title = {How to identify elliptical poems within a digital corpus of auditory poetry}, series = {Elektronische Sprachsignalverarbeitung 2019 (ESSV), Tagungsband der 30. Konferenz, Dresden, 3.-8. M{\"a}rz 2019}, booktitle = {Elektronische Sprachsignalverarbeitung 2019 (ESSV), Tagungsband der 30. Konferenz, Dresden, 3.-8. M{\"a}rz 2019}, editor = {Birkholz, Peter and Stone, Simon}, publisher = {TUDpress}, address = {Dresden, Germany}, isbn = {978-3-959081-57-3}, url = {http://nbn-resolving.de/urn:nbn:de:gbv:18-228-7-2579}, pages = {247 -- 254}, abstract = {Ellipses denote the omission of one or more grammatically necessary phrases. In this paper, we will demonstrate how to identify such ellipses as a rhythmical pattern in modern and postmodern free verse poetry by using data from lyrikline which contain the corresponding audio recording of each poem as spoken by the original author. We present a feature engineering approach based on literary analysis as well as a neural networks based approach for the identification of ellipses within the lines of a poem. A contrast class to the ellipsis is defined from poems consisting of complete and correct sentences. The feature-based approach used features derived from a parser such as verb, comma, and sentence ending punctuation. The classifier of neural networks is trained on the line level to integrate the textual information, the spoken recitation, and the pause information between lines, and to integrate information across the lines within the poem. A statistic analysis of poet's gender showed that 65\% of all elliptical poems were written by female poets. The best results, calculated by the weighted F-measure, for the classification of ellipsis with the contrast class is 0.94 with the neural networks based approach. The best results for classification of elliptical lines is 0.62 with the feature-based approach.}, language = {en} } @inproceedings{HusseinMeyerSickendiekBaumann, author = {Hussein, Hussein and Meyer-Sickendiek, Burkhard and Baumann, Timo}, title = {Identification of Concrete Poetry within a Modern-Poetry Corpus using Neural Networks}, series = {Proceedings of the Quantitative Approaches to Versification Conference}, booktitle = {Proceedings of the Quantitative Approaches to Versification Conference}, address = {Prague, Czech Republic}, pages = {95 -- 104}, abstract = {This work aims to discern the poetics of concrete poetry by using a corpus-based classification focusing on the two most important techniques used within concrete poetry: semantic decomposition and syntactic permutation. We demonstrate how to identify concrete poetry in modern and postmodern free verse. A class contrasting to concrete poetry is defined on the basis of poems with complete and correct sentences. We used the data from lyrikline, which contain both the written as well as the spoken form of poems as read by the original author. We explored two approaches for the identification of concrete poetry. The first is based on the definition of concrete poetry in literary theory by the extraction of various types of features derived from a parser, such as verb, noun, comma, sentence ending, conjunction, and asemantic material. The second is a neural network-based approach, which is theoretically less informed by human insight, as it does not have access to features established by scholars. This approach used the following inputs: textual information and the spoken recitation of poetic lines as well as information about pauses between lines. The results based on the neural network are more accurate than the feature-based approach. The best results, calculated by the weighted F-measure, for the classification of concrete poetry vis-{\`a}-vis the contrasting class is 0.96}, language = {en} } @misc{MeyerSickendiekHusseinBaumann, author = {Meyer-Sickendiek, Burkhard and Hussein, Hussein and Baumann, Timo}, title = {From Fluency To Disfluency: Ranking Prosodic Features Of Poetry By Using Neural Networks}, series = {Proceedings of the International Conference on Digital Humanities (DH 2019), Utrecht, the Netherlands 9-12 July, 2019}, journal = {Proceedings of the International Conference on Digital Humanities (DH 2019), Utrecht, the Netherlands 9-12 July, 2019}, doi = {10.34894/EGZNMI}, language = {en} }