正歌剧中的女高音：基于语料库的十八世纪人声类型研究
Soprano voices in opera seria: a corpus-based inquiry into eighteenth-century vocal types
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中文总结 AI 辅助
该研究基于约1700首十八世纪正歌剧咏叹调，采用岭逻辑回归分析人声类型、角色性别与创作风格的关系，发现角色性别在创作中存在编码，而歌手性别几乎无法识别。
中文摘要 AI 辅助
十八世纪意大利正歌剧以女高音为主导。尽管男性角色通常由阉人歌手扮演，女性角色由女性扮演，但反串十分普遍，形成了四种女高音配置，其中不同性别的表演者均可扮演不同性别的角色。我们假设作曲家会根据首演咏叹调的歌手以及角色的性别来调整创作。利用基于约1700首咏叹调构建的统计模型，我们分析了人声类型、角色性别与风格选择之间的关系，比较了多种监督学习方法并选择岭逻辑回归作为主要模型，该模型的性能与表现最佳的替代模型相当，同时支持对其系数进行解释和不确定性量化。结果显示存在不对称性：角色性别始终被编码在创作中，而歌手的性别几乎无法被识别。男性角色的咏叹调具有大音程跳跃、音程变异性和更宽的音域；女性角色的咏叹调则倾向于更高的最高音、小音程和旋律稳定性。女歌手比男性女高音演唱更高的音高，但这更多与角色塑造相关而非生理因素。
英文摘要
Eighteenth-century Italian opera seria was dominated by soprano voices. Although masculine roles were typically performed by castrati and feminine roles by women, cross-casting was common, producing four soprano configurations in which performers of either sex could portray characters of either gender. We hypothesize that composers tailored their writing both to the singers premiering their arias and to the characters' gender. Using statistical models built on approximately 1,700 arias, we analyze relationships between vocal typology, characters' gender, and stylistic choices, comparing supervised learning methods and selecting ridge logistic regression as our primary model, whose performance is competitive with that of the best-performing alternative while allowing for interpretation and uncertainty quantification of its coefficients. Results reveal an asymmetry: character gender is consistently encoded in the writing, while the singer's sex is barely recoverable. Masculine-character arias feature large melodic leaps, intervallic variability, and wider ranges; feminine-character arias favor higher maximum pitches, minor intervals, and melodic stability. Female singers sang higher pitches than male sopranos, but this correlates more with character portrayal than with physiology.
