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arXiv 提交日期: 2026-07-07
📄 Abstract - Umm... With Transformers? Insights from Filled Pause Use across Four Slavic Parliaments

Filled pauses (FPs) are a universal feature of spontaneous speech, yet most studies rely on small, single-language corpora, limiting the generalisability of their findings. We analyse ~4,000 hours of parliamentary speech across four related Slavic languages (Croatian, Czech, Polish, Serbian). FP occurrence is obtained via transformer-based automatic detection, while FP rate is modelled using Generalised Estimating Equations (GEE) with Mundlak correction to distinguish within- from between- speaker effects. We replicate a negative association of age and speech rate with FP rate, but find that gender effects are language-specific and directionally opposite to most prior literature. Novel analyses of sentiment, political orientation, and power status reveal a consistent positive association between sentiment and FP rate, alongside parliament-specific modulation by orientation and power status, with opposition speakers tending toward lower FP rates than governing coalition speakers.

顶级标签: natural language processing audio machine learning
详细标签: filled pauses parliamentary speech slavic languages sentiment analysis gender effects 或 搜索:

“嗯…”与Transformer模型?——四种斯拉夫语议会中填充停顿使用的洞察 / Umm... With Transformers? Insights from Filled Pause Use across Four Slavic Parliaments


1️⃣ 一句话总结

本研究利用Transformer模型自动检测四种斯拉夫语议会演讲中约4000小时的录音,发现说话者的年龄和语速与填充停顿(如“嗯”)的使用频率呈负相关,但性别的影响因语言而异且与传统研究结果相反;此外,积极情绪会促使更多填充停顿,而政治立场和权力地位(如执政党与反对党)对填充停顿的影响则因议会不同而有所差异。

源自 arXiv: 2607.05964