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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.16273 |
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| _version_ | 1866908839500054528 |
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| author | Vasic, Jelena Andjelic, Branislav Mancic, Ana Djurdjevic, Dusica Filipovic Mihic, Ljiljana Kovacevic, Aleksandar Maric, Nadja P. Maluckov, Aleksandra |
| author_facet | Vasic, Jelena Andjelic, Branislav Mancic, Ana Djurdjevic, Dusica Filipovic Mihic, Ljiljana Kovacevic, Aleksandar Maric, Nadja P. Maluckov, Aleksandra |
| contents | We analyze speech embeddings from structured clinical interviews of psychotic patients and healthy controls by treating language production as a high-dimensional dynamical process. Lyapunov exponent (LE) spectra are computed from word-level and answer-level embeddings generated by two distinct large language models, allowing us to assess the stability of the conclusions with respect to different embedding presentations. Word-level embeddings exhibit uniformly contracting dynamics with no positive LE, while answer-level embeddings, in spite of the overall contraction, display a number of positive LEs and higher-dimensional attractors. The resulting LE spectra robustly separate psychotic from healthy speech, while differentiation within the psychotic group is not statistically significant overall, despite a tendency of the most severe cases to occupy distinct dynamical regimes. These findings indicate that nonlinear dynamical invariants of speech embeddings provide a physics-inspired probe of disordered cognition whose conclusions remain stable across embedding models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_16273 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Lyapunov Spectral Analysis of Speech Embedding Trajectories in Psychosis Vasic, Jelena Andjelic, Branislav Mancic, Ana Djurdjevic, Dusica Filipovic Mihic, Ljiljana Kovacevic, Aleksandar Maric, Nadja P. Maluckov, Aleksandra Adaptation and Self-Organizing Systems Computation and Language We analyze speech embeddings from structured clinical interviews of psychotic patients and healthy controls by treating language production as a high-dimensional dynamical process. Lyapunov exponent (LE) spectra are computed from word-level and answer-level embeddings generated by two distinct large language models, allowing us to assess the stability of the conclusions with respect to different embedding presentations. Word-level embeddings exhibit uniformly contracting dynamics with no positive LE, while answer-level embeddings, in spite of the overall contraction, display a number of positive LEs and higher-dimensional attractors. The resulting LE spectra robustly separate psychotic from healthy speech, while differentiation within the psychotic group is not statistically significant overall, despite a tendency of the most severe cases to occupy distinct dynamical regimes. These findings indicate that nonlinear dynamical invariants of speech embeddings provide a physics-inspired probe of disordered cognition whose conclusions remain stable across embedding models. |
| title | Lyapunov Spectral Analysis of Speech Embedding Trajectories in Psychosis |
| topic | Adaptation and Self-Organizing Systems Computation and Language |
| url | https://arxiv.org/abs/2602.16273 |