Abstract
Middle High German (MHG) epic poetry presents a unique solution to the linguistic changes underpinning the transition from classical Latin poetry, based on syllable length, into later vernacular rhythmic poetry, based on phonological stress. The predominating pattern in MHG verse is the alternation between stressed and unstressed syllables, but syllable length also plays a crucial role. There are a total of eight possible metrical values. Single or half mora syllables can carry any one of three types of stress, resulting in six combinations. The seventh value is a double mora, i.e., a long stressed syllable. The eighth value is an elided syllable. We construct a supervised Conditional Random Fields (CRF) model to predict the metrical value of syllables, and subsequently investigate medieval German poets’ use of semantic and sonorous emphasis through meter. The features used are: 1) the syllable’s position within the line, 2) the syllable’s length in characters, 3) the syllable’s characters, 4) elision (last two characters of previous syllable and first two characters of focal syllable), 5) syllable weight, and 6) word boundaries. Additional metrical rules are enforced and marginal probabilities are calculated to yield the most likely legal scansion of a line. The model achieves a macro average F-score of .925 on internal cross-validation and .909 on held-out testing data. We determine that trochaic alternation with a one syllable anacrusis and words carrying clear stress assignment are the easiest for the model to scan. Lines with multiple double morae of syllables with few characters are the most difficult. We then rank all the epic poetry in the Mittelhochdeutsche Begriffsdatenbank (MHDBDB) by the difficulty of the meter. Finally, we investigate the double mora, which MHG poets used to draw attention to chosen concepts. We conclude that poets generally chose to use the double mora to emphasize highly sonorant words.
Highlights
Poetic meter in the Middle High German (MHG) tradition has always been a contentious and complex subject, as it requires a nuanced knowledge of MHG literature, a strong understanding of MHG linguistics, phonology, and knowledge of the musical practices of the period1
The preferred Conditional Random Field (CRF) model achieves an F-score of example, if the model can see that there are likely two half morae at the end of a foot, the beginning of the foot is likely one mora and not a double mora
Future work might consider an alternative in sacrificing interpretability for accuracy utilizing a Bidirectional Long Short Term Memory (BLSTM) neural network, though this is not attempted in this project because the CRF model proves very accurate when considering Cohen’s Kappa. 47All features are encoded as categorical
Summary
Poetic meter in the Middle High German (MHG) tradition has always been a contentious and complex subject, as it requires a nuanced knowledge of MHG literature, a strong understanding of MHG linguistics, phonology, and knowledge of the musical practices of the period. While this paper does not attempt to fully unite these diverse fields, it does seek to take careful consideration of each in developing a computational model to better understand how medieval German poets crafted their words into meter, and in turn aid us in our own reading of the text. The goal of any such model is not to establish an absolute truth about a historical language; the goal is to automatically reproduce the annotation decisions of scholars on a large scale. Annotating the entire MHG epic corpus would allow us to better understand any rules that do exist as well as the challenges any particular text poses. Automatic annotation would support a large scale analysis on how specific metrical values and meter types are invoked in different contexts. This paper seeks to answer these questions and others through a large scale analysis of automatically scanned poetry Scholars often discuss how changes in meter, metrical values, or specific cadences are triggered in specific scenes, but can we measure this complexity? MHG meter provides for fascinating flexibility in emphasis, but did authors have preferences for different metrical values? Are certain texts or passages intentionally crafted to be more difficult to scan? This paper seeks to answer these questions and others through a large scale analysis of automatically scanned poetry
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