AI schizophrenia diagnosis through speech features F0 and MFCC

Teixeira, Felipe; Fernandes, Joana; Santos, Adriana; Abreu, J.; Soares, Salviano; Teixeira, João Paulo

http://hdl.handle.net/10198/36720

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Resumo(s)

Schizophrenia affects over 20 million people globally and is often undetected in its early stages. Speech has unique characteristics that can help identify mental illnesses, including schizophrenia, which usually manifests through slower, repetitive, or incoherent speech patterns. By extracting acoustic features like fundamental frequency (F0) and Mel Frequency Cepstral Coefficients (MFCCs) and applying machine learning, we can identify patterns that distinguish healthy individuals from those with schizophrenia. In this work, was achieved 95% accuracy to classify between schizophrenic and healthy people through speech.

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http://hdl.handle.net/10198/36720

Citação

Teixeira, Felipe; Fernandes, Joana; Santos, Adriana; Abreu, J.; Soares, Salviano; Teixeira, João Paulo (2025). AI schizophrenia diagnosis through speech features F0 and MFCC. In International Conference on Demographic Transition, Health and Technologies, ICDTHT 2025. p. 117-126. ISBN 978-303194900-5. DOI: 10.1007/978-3-031-94901-2_10