arXiv cs.CL· Debasmita Bhattacharya, Siying Ding, Alayna Nguyen, Julia Hirschberg·· 12 小时前AI 评分18
人类与分类模型在语码转换语音中的趋同行为跨语言对比研究
A Cross-lingual Comparison of Human and Classification Model Entrainment Behavior in Code-switched Speech Settings
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研究将西班牙语-英语对话中的趋同行为框架扩展至普通话-英语、印地语-英语和西班牙语-英语三组对话，发现词汇层面的趋同可跨语言泛化，而声学韵律与语码转换风格层面的趋同则随语境变化。
正文 · 原文
Abstract:Conversational entrainment is well-studied in monolingual and written contexts, but remains underexplored in spoken code-switching (CSW). We present a cross-lingual analysis of entrainment in Mandarin-English, Hindi-English, and Spanish-English dialogue, replicating and extending an established Spanish-English framework (Bhattacharya et al., 2024) to two new language pairs, and show that, while lexical entrainment generalizes across language pairs, entrainment over acoustic-prosodic and CSW style aspects exhibits context-specific variation. We build on these findings by asking whether classification models capture these human behavioral patterns. Using feature importance and ablation analyses, we find that classical and Transformer-based classifiers detect entrainment reasonably well but consistently prioritize features other than those most salient to human entraining behavior. Our approach introduces a human-grounded framework for evaluating model decision-making in multilingual stylistic contexts, and suggests challenges for developing conversational agents capable of producing naturalistic code-switched speech.
| Comments: | Camera-ready for EMNLP 2026 |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2607.25202 [cs.CL] |
| (or arXiv:2607.25202v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2607.25202 arXiv-issued DOI via DataCite |
Submission history
From: Debasmita Bhattacharya [view email]
[v1]
Tue, 28 Jul 2026 02:16:41 UTC (708 KB)
[v2]
Fri, 23 Oct 2026 15:18:31 UTC (753 KB)
来源：arXiv cs.CL · arxiv.org