24@DMMS'2023pb Detection of mental disorders based on speech

project type: reasarch

edition: 2023pb

number of students in project 1 - 10

manager: Anna Rekiel

The research project aims to analyze the
links between speech and the association with mental disorders. Among the tasks
envisioned is analyzing the speech signal (and speech) of people diagnosed with
mental disorders using signal processing (and speech analysis). Further expected
is the extraction of features associated with the speech signal and the use of
learning algorithms.

Tasks to be performed:

Literature review on the subject

Review of available databases of mental disorders

Selecting a database for speech signal
analysis

Signal/speech analysis

Preparation of learning algorithm
architectures

Speech detection of people with mental
disorders using machine learning

Analysis of the obtained results

Conclusions

Preparation of the publication

Literature:

Fu, J., Yang, S., He, F. et
al. Sch-net: a deep learning
architecture for automatic detection of schizophrenia. BioMed
Eng OnLine 20, 75 (2021). https://doi.org/10.1186/s12938-021-00915-2
, https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-021-00915-2

Li Y, Lin Y, Ding H, Li C. Speech
databases for mental disorders: A systematic review. Gen Psychiatr. 2019 Jul
22;32(3):e100022. doi: 10.1136/gpsych-2018-100022. PMID: 31423472; PMCID:
PMC6677935., https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677935/