A Metrical Analysis of Medieval German Poetry Using Supervised Learning

C. Hench, Alex Estes
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引用次数: 1

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.
用监督学习法分析中世纪德国诗歌的格律
中古高地德语(MHG)史诗为语言变化提供了一种独特的解决方案,这种变化支撑着从基于音节长度的古典拉丁诗歌到后来基于语音重音的白话韵律诗歌的过渡。MHG诗的主要形式是重读音节和非重读音节的交替,但音节长度也起着至关重要的作用。总共有八个可能的格律值。单音节或半音节可以携带三种重音中的任何一种,从而产生六种组合。第七个值是双音节,即长重读音节。第八个值是省略的音节。我们构建了一个有监督的条件随机场(CRF)模型来预测音节的韵律值,并随后研究了中世纪德国诗人通过韵律使用语义和铿锵重音。所使用的特征是:1)音节在行的位置,2)音节的字符长度,3)音节的字符,4)省略(前一个音节的后两个字符和焦点音节的前两个字符),5)音节的权重,6)单词的边界。附加的格律规则被强制执行,边际概率被计算以产生最可能合法的一条线。该模型在内部交叉验证上的宏观平均f值为0.925,在持有测试数据上的宏观平均f值为0.909。我们确定了一个音节重叠的扬格交替和带有明确重音分配的单词是最容易被模型扫描的。具有多个双音节和几个字符的行是最困难的。然后,我们根据韵律的难易程度对所有的史诗进行排名。最后,我们研究了MHG诗人用来吸引人们注意所选概念的双重道德。我们得出的结论是,诗人通常选择使用双重语气来强调高度发音的单词。
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