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Updated: Apr 18, 2026
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Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
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From Voice to Self: An Integrative Framework on Self-Voice Processing
1Linguistic Research Infrastructure, University of Zurich.
Summary
Understanding the self-voice is crucial for communication and identity. This study proposes a new framework, integrating auditory, motor, memory, multisensory, and self-concept components for better self-voice processing.
Area of Science:
- Psychological Science
- Neuroscience
- Voice Technology
Background:
- The self-voice is vital for communication and identity but is understudied.
- AI-generated voices necessitate a deeper understanding of self-voice perception.
- Disruptions in self-voice processing link to clinical conditions like psychosis and autism.
Purpose of the Study:
- To address methodological and conceptual challenges in self-voice research.
- To propose an integrative framework for understanding self-voice processing.
- To bridge psychology, neuroscience, and voice technology.
Main Methods:
- Decomposition of the self-voice into five interacting components: auditory, motor control, memory, multisensory integration, and self-concept.
- Review of the functional and neural basis of each component.
- Examination of how these components converge in brain networks.
Main Results:
- The proposed framework integrates multiple components of self-voice processing.
- It highlights the convergence of these components within distributed brain networks.
- It addresses limitations in current self-voice research methodologies and conceptualizations.
Conclusions:
- An integrative framework is proposed to advance self-voice research.
- This framework enhances understanding across psychology, neuroscience, and clinical research.
- It provides a foundation for future work in digital voice environments.
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