{"slug": "a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code", "title": "A Cross-lingual Comparison of Human and Classification Model Entrainment Behavior in Code-switched Speech Settings", "summary": "A new arXiv preprint (2607.25202v1) presents a cross-lingual analysis of conversational entrainment in Mandarin-English, Hindi-English, and Spanish-English code-switched speech, finding that lexical entrainment generalizes across language pairs but acoustic-prosodic and code-switching style entrainment varies by context. The study also shows that classical and Transformer-based classifiers detect entrainment reasonably well but prioritize different features than humans, highlighting challenges for developing naturalistic code-switched conversational agents.", "body_md": "arXiv:2607.25202v1 Announce Type: new\nAbstract: Conversational entrainment is well-studied in monolingual and written contexts, but remains underexplored in spoken code-switching (CSW). We present a novel cross-lingual analysis of entrainment in Mandarin-English, Hindi-English, and Spanish-English dialogue 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. Applying 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 future challenges for developing conversational agents capable of producing naturalistic code-switched speech.", "url": "https://wpnews.pro/news/a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code", "canonical_source": "https://arxiv.org/abs/2607.25202", "published_at": "2026-07-29 04:00:00+00:00", "updated_at": "2026-07-29 04:26:56.643589+00:00", "lang": "en", "topics": ["artificial-intelligence", "natural-language-processing", "machine-learning"], "entities": ["arXiv"], "alternates": {"html": "https://wpnews.pro/news/a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code", "markdown": "https://wpnews.pro/news/a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code.md", "text": "https://wpnews.pro/news/a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code.txt", "jsonld": "https://wpnews.pro/news/a-cross-lingual-comparison-of-human-and-classification-model-entrainment-in-code.jsonld"}}