ArticleFrontiers in psychiatry2022
The applicability of the Beck Depression Inventory and Hamilton Depression Scale in the automatic recognition of depression based on speech signal processing.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance of Automatic Speech Analysis in Detecting Depression: Systematic Review and Meta-Analysis.JMIR mental health · 2025Pooled it
- The role of idioms in reducing depression in university students: a study on group cognitive behavioral therapy.BMC psychology · 2025Trial
- ACES: ascertaining diagnosis classification with elicited speech in individuals with heterogeneous, comorbid psychiatric disorders.Psychiatry research · 2026Article
- Prevalence and Correlates of Mental Health Issues Among University Students in Punjab, Pakistan: Insights into Academic Performance and Psychological Well-Being.Healthcare (Basel, Switzerland) · 2026Article
- The correlation between depression and haemodialysis adequacy in chronic kidney disease patients in South Africa.Health SA = SA Gesondheid · 2026Article
- Change ofFrontiers in psychology · 2026Article
- Multilevel brain functional connectivity and task-based representations explaining heterogeneity in major depressive disorder.Translational psychiatry · 2025Article
- Siamese Neural Network for Speech-Based Depression Classification and Severity Assessment.Journal of healthcare informatics research · 2024Article
- Risk of depression after Parkinson's disease, stroke, multiple sclerosis, and migraine in an Iranian population and assess psychometric characteristics of three prevalent depression questionnaires.IBRO neuroscience reports · 2024Article
- Multitask and Transfer Learning Approach for Joint Classification and Severity Estimation of Dysphonia.IEEE journal of translational engineering in health and medicine · 2024Article
- Are probiotics beneficial for obese patients with major depressive disorder? Opinion for future implications and strategies.Frontiers in nutrition · 2023Article
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5 authors.
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Abstract
Depression is a growing problem worldwide, impacting on an increasing number of patients, and also affecting health systems and the global economy. The most common diagnostical rating scales of depression are self-reported or clinician-administered, which differ in the symptoms that they are sampling. Speech is a promising biomarker in the diagnostical assessment of depression, due to non-invasiveness and cost and time efficiency. In our study, we try to achieve a more accurate, sensitive model for determining depression based on speech processing. Regression and classification models were also developed using a machine learning method. During the research, we had access to a large speech database that includes speech samples from depressed and healthy subjects. The database contains the Beck Depression Inventory (BDI) score of each subject and the Hamilton Rating Scale for Depression (HAMD) score of 20% of the subjects. This fact provided an opportunity to compare the usefulness of BDI and HAMD for training models of automatic recognition of depression based on speech signal processing. We found that the estimated values of the acoustic model trained on BDI scores are closer to HAMD assessment than to the BDI scores, and the partial application of HAMD scores instead of BDI scores in training improves the accuracy of automatic recognition of depression.
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