TY - CHAP A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo ED - Birkholz, Peter ED - Stone, Simon T1 - How to identify elliptical poems within a digital corpus of auditory poetry T2 - Elektronische Sprachsignalverarbeitung 2019 (ESSV), Tagungsband der 30. Konferenz, Dresden, 3.-8. März 2019 N2 - 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. Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:18-228-7-2579 UR - http://www.essv.de/paper.php?id=88 SN - 978-3-959081-57-3 SP - 247 EP - 254 PB - TUDpress CY - Dresden, Germany ER - TY - CHAP A1 - Baumann, Timo A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein T1 - How to Identify Speech When Translating Unpunctuated Poetry T2 - Proceedings of Elektronische Sprachsignalverarbeitung: Tagungsband der 31. Konferenz, Magdeburg, 4.-6. März 2020 N2 - A large proportion of (post)-modern poetry contains no or hardly any punctuation. In our contribution, we will investigate how well punctuation information can be recovered for postmodern poetry based on the information contained in the text and speech of free verse poems. We use the world's largest corpus of spoken (post-)modern poetry from our partner lyrikline which contains the corresponding audio recording of each poem as spoken by the original author and features translations for many of the poems. We identify lines that contain a phrase break in the middle of the poetic line, which may already be helpful for philological analysis on one hand, and identify the position of the break in the line on the other hand. We select those poetic lines that contain one or more punctuation characters that typically indicate a phrase break in poetry (.,;:!?/) somewhere in the middle (rather than only at the end of the line) as our target class. We train a neural network (bidirectional recurrent neural network (RNN) based on gated recurrent units (GRU) with attention) that combines audio and textual features to identify the punctuation with the goal of applying it to reconstruct them within a corpus of unpunctuated poems. Our results clearly indicate that speech is helpful for recovering the constituency structure of post-modern poetry that is partially obfuscated by missing punctuation. Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:18-228-7-2587 UR - http://www.essv.de/paper.php?id=452 SP - 165 EP - 172 PB - Förderverein Elektronische Sprachsignalverabeitung e.V. CY - Magdeburg, Germany ER - TY - CHAP A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo T1 - Tonality in Language: The Generative Theory of Tonal Music as a Framework for Prosodic Analysis of Poetry T2 - 6th International Symposium on Tonal Aspects of Languages (TAL 2018), 18-20 June 2018, Berlin, Germany N2 - This contribution focuses on structural similarities between tonality and cadences in music on the one hand, and rhythmical patterns in poetic languages respectively poetry on the other hand. We investigate two exemplary rhythmical patterns in modern and postmodern poetry to detect these tonality-like features in poetic language: The Parlando and the Variable Foot. German poems readout from the original poets are collected from the webpage of our partner lyrikline. We compared these rhythmical features with tonality rules, explained in two important theoretical volumes: The Generative Theory of Tonal Music and the Rhythmic Phrasing in English Verse. Using both volumes, we focused on a certain combination of four different features: The grouping structure, the metrical structure, the time-span-variation and the prolongation, in order to detect the two important rhythmical patterns which use tonality-like features in poetic language (Parlando and Variable Foot). Different features including pause and parser information are used in this classification process. The best classification result, calculated by the f-measure, for Parlando and Variable Foot is 0.69. KW - tonality in poetic language KW - prosodic patterns in postwar poems KW - automatic detection of prosodic features Y1 - 2018 U6 - https://doi.org/10.21437/TAL.2018-36 SP - 178 EP - 182 PB - ISCA ER - TY - CHAP A1 - Baumann, Timo A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard T1 - Analysis of Rhythmic Phrasing: Feature Engineering vs. Representation Learning for Classifying Readout Poetry T2 - Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL-2018), August 25, 2018, Santa Fe, New Mexico, USA N2 - We show how to classify the phrasing of readout poems with the help of machine learning algorithms that use manually engineered features or automatically learn representations. We investigate modern and postmodern poems from the webpage lyrikline, and focus on two exemplary rhythmical patterns in order to detect the rhythmic phrasing: The Parlando and the Variable Foot. These rhythmical patterns have been compared by using two important theoretical works: The Generative Theory of Tonal Music and the Rhythmic Phrasing in English Verse. Using both, we focus on a combination of four different features: The grouping structure, the metrical structure, the time-span-variation, and the prolongation in order to detect the rhythmic phrasing in the two rhythmical types. We use manually engineered features based on text-speech alignment and parsing for classification. We also train a neural network to learn its own representation based on text, speech and audio during pauses. The neural network outperforms manual feature engineering, reaching an f-measure of 0.85. Y1 - 2018 UR - https://aclanthology.org/W18-4505 SP - 44 EP - 49 PB - Association for Computational Linguistics CY - Santa Fe, New Mexico ER - TY - CHAP A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo T1 - Identification of Concrete Poetry within a Modern-Poetry Corpus using Neural Networks T2 - Proceedings of the Quantitative Approaches to Versification Conference N2 - 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-à-vis the contrasting class is 0.96 Y1 - 2019 UR - https://versologie.cz/conference2019/proceedings/hussein-meyer-sickendiek-baumann.pdf SP - 95 EP - 104 CY - Prague, Czech Republic ER - TY - CHAP A1 - Baumann, Timo A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Elbeshausen, Jasper ED - Draude, Claude ED - Lange, Martin ED - Sick, Bernhard T1 - A Tool for Human-in-the-Loop Analysis and Exploration of (not only) Prosodic Classifications for Post-modern Poetry T2 - Informatik 2019 : 50 Jahre Gesellschaft für Informatik Workshop-Beiträge Fachtagung vom 23.-26. September 2019 in Kassel N2 - 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. KW - classification KW - data mining KW - free verse poetry KW - human-in-the-loop KW - rhythmical patterns Y1 - 2019 UR - https://dl.gi.de/bitstream/handle/20.500.12116/25047/paper03_08.pdf?sequence=1&isAllowed=y SN - 978-3-88579-689-3 SP - 151 EP - 156 PB - Gesellschaft für Informatik CY - Bonn ER - TY - CHAP A1 - Baumann, Timo A1 - Meyer-Sickendiek, Burkhard ED - Krauwer, Steven ED - Fišer, Darja T1 - Deep Learning meets Post-modern Poetry T2 - TwinTalks 2020: Understanding and Facilitating Collaboration in Digital Humanities 2020, proceedings of the Twin Talks 2 and 3 workshops at DHN 2020 and DH 2020, Ottawa Canada and Riga Latvia, July 23 and October 20, 2020 N2 - We summarize our project Rhythmicalizer in which we analyze a corpus of post-modern poetry in a combination of qualitative hermeneutical and computational methods, as we have run the project over the course of the past three years (and preparing it for some time before that). Interdisciplinary work is always challenging and we here focus on some of the highlights of our collaboration. KW - Literary Studies KW - Machine Learning KW - Meta-Research Y1 - 2020 UR - http://ceur-ws.org/Vol-2717/paper03.pdf SN - 1613-0073 SP - 30 EP - 36 PB - RWTH Aachen ER - TY - GEN A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo A1 - Hussein, Hussein T1 - Requirements on the Punctuation Reconstruction for the Translation of Post-modern Poetry T2 - DHd 2020 ; Spielräume ; Digital Humanities zwischen Modellierung und Interpretation ; Konferenzabstracts ; Universität Paderborn 02. bis 06. März 2020 Y1 - 2020 SN - 978-3-945437-07-0 U6 - https://doi.org/10.5281/zenodo.4621722 PB - Universität Paderborn CY - Paderborn ER - TY - GEN A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein A1 - Baumann, Timo T1 - From Fluency To Disfluency: Ranking Prosodic Features Of Poetry By Using Neural Networks T2 - Proceedings of the International Conference on Digital Humanities (DH 2019), Utrecht, the Netherlands 9-12 July, 2019 Y1 - 2019 U6 - https://doi.org/10.34894/EGZNMI ER - TY - CHAP A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo T1 - Free Verse and Beyond: How to Classify Post-modern Spoken Poetry T2 - Proceedings of Speech Prosody: Tokyo, Japan, 25-28 May 2020 N2 - This paper presents the classification of rhythmical patterns detected in post-modern spoken poetry by means of machine learning algorithms that use manually engineered features or automatically learnt representations. We used the world's largest corpus of spoken poetry from our partner lyrikline. We identified nine rhythmical patterns within a spectrum raging from a more fluent to a more disfluent poetic style. The text data analyzed by a statistical parser. Prosodic features of rhythmical patterns are identified by using the parser information. For the classification of rhythmical patterns, we used a neural networks-based approach which use text, audio, and pause information between poetic lines as features. Different combinations of features as well as the integration of feature engineering in the neural networks-based approach are tested. We compared the performance of both approaches (feature-based and neural network-based) using combinations of different features. The results show – by using the weighted average of f-measure for the evaluation – that the neural networks-based approach performed much better in classification of rhythmical patterns. The important improvement of the classification results lies in the use of the audio information. The integration of feature engineering in the neural networks-based approach yielded a very small result improvement. Y1 - 2020 U6 - https://doi.org/10.21437/SpeechProsody.2020-141 SP - 690 EP - 694 PB - ISCA ER - TY - CHAP A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein A1 - Baumann, Timo ED - Eibl, Maximilian ED - Gaedke, Martin T1 - Rhythmicalizer: Data Analysis for the Identification of Rhythmic Patterns in Readout Poetry T2 - INFORMATIK 2017, Tagung vom 25.- 29. September 2017 in Chemnitz T2 - GI-Edition Lecture notes in informatics. Proceedings ; volume P-275 N2 - The most important development in modern and postmodern poetry is the replacement of traditional meter by new rhythmical patterns. Ever since Walt Whitman's Leaves of Grass (1855), modern (nineteenth-to twenty-first-century) poets have been searching for novel forms of prosody, accent, rhythm, and intonation. Along with the rejection of older metrical units such as the iamb or trochee, a structure of lyrical language was developed that renounced traditional forms like rhyme and meter. This development is subsumed under the term free verse prosody. Our project will test this theory by applying machine learning or deep learning techniques to a corpus of modern and postmodern poems as read aloud by the original authors. To this end, we examine “lyrikline”, the most famous online portal for spoken poetry. First, about 17 different patterns being characteristic for the lyrikline-poems have been identified by the philological scholar of this project. This identification was based on a certain philological method including three different steps: a) grammetrical ranking; b) rhythmic phrasing; and c) mapping rubato and prosodic phrasing. In this paper we will show how to combine this philological and a digital analysis by using the prosody detection available in speech processing technology. In order to analyse the data, we want to use different tools for the following tasks: PoS-tagging, alignment, intonation, phrases and pauses, and tempo. We also analyzed the lyrikline-data by identifying the occurrence of the mentioned patterns. This analysis is a first step towards an automatic classification based on machine learning or deep learning techniques. Y1 - 2017 SN - 978-3-88579-669-5 U6 - https://doi.org/10.18420/in2017_218 SP - 2189 EP - 2200 PB - Gesellschaft für Informatik CY - Bonn ER - TY - CHAP A1 - Baumann, Timo A1 - Meyer-Sickendiek, Burkhard T1 - Large-scale Analysis of Spoken Free-verse Poetry T2 - Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities, Osaka, Japan, December 11-17 2016 N2 - Most modern and post-modern poems have developed a post-metrical idea of lyrical prosody that employs rhythmical features of everyday language and prose instead of a strict adherence to rhyme and metrical schemes. This development is subsumed under the term free verse prosody. We present our methodology for the large-scale analysis of modern and post-modern poetry in both their written form and as spoken aloud by the author. We employ language processing tools to align text and speech, to generate a null-model of how the poem would be spoken by a naïve reader, and to extract contrastive prosodic features used by the poet. On these, we intend to build our model of free verse prosody, which will help to understand, differentiate and relate the different styles of free verse poetry. We plan to use our processing scheme on large amounts of data to iteratively build models of styles, to validate and guide manual style annotation, to identify further rhythmical categories, and ultimately to broaden our understanding of free verse poetry. In this paper, we report on a proof-of-concept of our methodology using smaller amounts of poems and a limited set of features. We find that our methodology helps to extract differentiating features in the authors’ speech that can be explained by philological insight. Thus, our automatic method helps to guide the literary analysis and this in turn helps to improve our computational models. Y1 - 2016 UR - https://aclanthology.org/W16-4017 SP - 125 EP - 130 PB - The COLING 2016 Organizing Committee ER - TY - CHAP A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard A1 - Baumann, Timo T1 - Automatic Detection of Enjambment in German Readout Poetry T2 - Proceedings of Speech Prosody, 2018, Poznán N2 - One of the most important patterns in ancient as well as modern poetry is the enjambment, the continuation of a sentence beyond the end of a line, couplet, or stanza. The paper reports first activities towards the development of a digital tool to analyze the accentuation of poetic enjambments in readout poetry. The aim in this contribution is to recognize two forms of enjambment (emphasized and unemphasized) in poems using audio and text data. We use data from lyrikline which is a major online portal for spoken poetry whereas poems are read aloud by the original authors. We identified by hermeneutical means based on literary analysis a total of 69 poems being characteristic for the use of enjambments in modern and postmodern German poetry and train classifiers to differentiate the emphasized/unemphasized ategorization. A remarkable result of our automated analyses (and to our knowledge the first data-driven analysis of this kind) is the identification of a cultural difference in the accentuation of enjambments: statistically speaking, poets from the former GDR tend to emphasize the enjambment, whereas poets from the FRG do not. We use features derived from speech-to-text alignment and statistical parsing information such as pause lengths, number of lines with verbs, and number of lines with punctuation. The best classification results, calculated by the F-measure, for the both types of enjambment (emphasized/unemphasized) is 0.69. KW - modern and postmodern poetry KW - free verse prosody KW - emphasized and unemphasized enjambment Y1 - 2018 U6 - https://doi.org/10.21437/SpeechProsody.2018-67 SP - 329 EP - 333 PB - ISCA ER - TY - CHAP A1 - Baumann, Timo A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard T1 - Analysing the Focus of a Hierarchical Attention Network: the Importance of Enjambments When Classifying Post-modern Poetry T2 - Proceedings of Interspeech, 2018, Hyderabad N2 - After overcoming the traditional metrics, modern and postmodern poetry developed a large variety of ‘free verse prosodies’ that falls along a spectrum from a more fluent to a more disfluent and choppy style. We present a method, grounded in philological analysis and theories on cognitive (dis)fluency, to analyze this ‘free verse spectrum’ into six classes of poetic styles as well as to differentiate three types of poems with enjambments. We use a model for automatic prosodic analysis of spoken free verse poetry which uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We then analyze and fine-tune the model with a particular focus on enjambments and in two ways: we drill down on classification performance by analyzing whether the model focuses on similar traits of poems as humans would, specifically, whether it internally builds a notion of enjambment. We find that our model is similarly good as humans in finding enjambments; however, when we employ the model for classifying enjambment-dominated poem types, it does not pay particular attention to those lines. Adding enjambment labels to the training only marginally improves performance, indicating that all other lines are similarly informative for the model. KW - digital humanities KW - free verse poetry KW - prosodic analysis KW - enjambment detection KW - hierarchical attention network Y1 - 2018 U6 - https://doi.org/10.21437/Interspeech.2018-2533 SP - 2162 EP - 2166 ER - TY - CHAP A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein A1 - Baumann, Timo ED - Burghardt, M. ED - Müller-Birn, C. T1 - Analysis and Classification of Prosodic Styles in Post-modern Spoken Poetry T2 - INF-DH 2018 Workshopband N2 - We present our research on computer-supported analysis of prosodic styles in post-modern poetry. Our project is unique in making use of both the written as well as the spoken form of the poem as read by the original author. In particular, we use speech and natural language processing technology to align speech and text and to perform textual analyses. We then explore, based on literary theory, the quantitative value of various types of features in differentiating various prosodic classes of post-modern poetry using machine-learning techniques. We contrast this feature-driven approach with a theoretically less informed neural networks-based approach and explore the relative strengths of both models, as well as how to integrate higher-level knowledge into the NN. In this paper, we give an overview of our project, our approach, and particularly focus on the challenges encountered and lessons learned in our interdisciplinary endeavour. The classification results of the rhythmical patterns (six classes) using NN-based approaches are better than by feature-based approaches. KW - modern and postmodern poetry KW - free verse prosody KW - rhythmical patters Y1 - 2018 U6 - https://doi.org/10.18420/infdh2018-09 PB - Gesellschaft für Informatik e.V ER - TY - CHAP A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein A1 - Baumann, Timo ED - Berton, André ED - Haiber, Udo ED - Minker, Wolfgang T1 - Recognizing Modern Sound Poetry with LSTM Networks T2 - Proceedings of Elektronische Sprachsignalverarbeitung (ESSV) N2 - 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 compositions. 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. KW - Sprachverarbeitung Y1 - 2018 UR - http://www.essv.de/paper.php?id=407 SN - 978-3-959081-28-3 SP - 192 EP - 199 PB - TUDpress CY - Ulm, Germany ER - TY - CHAP A1 - Baumann, Timo A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard T1 - Style Detection for Free Verse Poetry from Text and Speech T2 - Proceedings of the 27th International Conference on Computational Linguistics (COLING), 20-26.08.2018, Santa Fe, New Mexico, USA N2 - Modern and post-modern free verse poems feature a large and complex variety in their poetic prosodies that falls along a continuum from a more fluent to a more disfluent and choppy style. As the poets of modernism overcame rhyme and meter, they oriented themselves in these two opposing directions, creating a free verse spectrum that calls for new analyses of prosodic forms. We present a method, grounded in philological analysis and current research on cognitive (dis)fluency, for automatically analyzing this spectrum. We define and relate six classes of poetic styles (ranging from parlando to lettristic decomposition) by their gradual differentiation. Based on this discussion, we present a model for automatic prosodic classification of spoken free verse poetry that uses deep hierarchical attention networks to integrate the source text and audio and predict the assigned class. We evaluate our model on a large corpus of German author-read post-modern poetry and find that classes can reliably be differentiated, reaching a weighted f-measure of 0.73, when combining textual and phonetic evidence. In our further analyses, we validate the model’s decision-making process, the philologically hypothesized continuum of fluency and investigate the relative importance of various features. Y1 - 2018 UR - https://aclanthology.org/C18-1164.pdf SP - 1929 EP - 1940 ER - TY - JOUR A1 - Meyer-Sickendiek, Burkhard A1 - Hussein, Hussein A1 - Baumann, Timo T1 - Towards the Creation of a Poetry Translation Mapping System JF - Archives of Data Science, Series A N2 - The translation of poetry is a complex, multifaceted challenge: the translated text should communicate the same meaning, similar metaphoric expressions, and also match the style and prosody of the original poem. Research on machine poetry translation is existing since 2010, but for four reasons it is still rather insufficient: 1. The few approaches existing completely lack any knowledge about current developments in both lyric theory and translation theory. 2. They are based on very small datasets. 3. They mostly ignored the neural learning approach that superseded the long-standing dominance of phrase-based approaches within machine translation. 4. They have no concept concerning the pragmatic function of their research and the resulting tools. Our paper describes how to improve the existing research and technology for poetry translations in exactly these four points. With regards to 1) we will describe the “Poetics of Translation”. With regards to 2) we will introduce the Worlds largest corpus for poetry translations from lyrikline. With regards to 3) we will describe first steps towards a neural machine translation of poetry. With regards to 4) we will describe first steps towards the development of a poetry translation mapping system. Y1 - 2018 U6 - https://doi.org/10.5445/KSP/1000087327/21 SN - 2363-9881 VL - 5 IS - 1 SP - 1 EP - 15 PB - Towards the Creation of a Poetry Translation Mapping System ER - TY - CHAP A1 - Baumann, Timo A1 - Hussein, Hussein A1 - Meyer-Sickendiek, Burkhard ED - Schneider, Birgit ED - Löffler, Beate ED - Mager, Tino ED - Hein, Carola T1 - Free Verse Prosodies: Identifying and Classifying Spoken Poetry Using Literary and Computational Perspectives (Rhythmicalizer) T2 - Mixing Methods: Practical Insights from the Humanities in the Digital Age N2 - At least 80% of modern and postmodern poems exhibit neither rhyme nor metrical schemes such as iamb or trochee. However, does this mean that they are free of any rhythmical features?TheUS American research onfree verse prosody claimsthe opposite: Modern poets like Whitman, the Imagists, the Beat poets and contemporary Slam poets have developed a postmetrical idea of prosody, using rhythmical features of everyday language, prose, and musical styles like Jazz or Hip Hop. It has spawned a large and complex variety intheir poetic prosodies which,however,appearto bemuchharderto quantify and regularize than traditional patterns. In our project, we examinethe largest portal for spoken poetry Lyrikline and analysed and classified such rhythmical patterns by using pattern recognition and classification techniques. We integrate a human-in-the-loop approach in which we interleave manual annotation with computational modelling and data-based analysis. Our results are integrated into the website of Lyrikline. Our follow-up project makes our research results available to a wider audience, in particular to high school-level teaching. Y1 - 2023 U6 - https://doi.org/10.1515/9783839469132-018 SP - 167 EP - 186 PB - Bielefeld University Press CY - Bielefeld ER -