Shunji Mitsuyoshi
Biographic Data
| ID | 7913816 |
|---|---|
| NAME | Shunji Mitsuyoshi |
| GIVEN NAMES | Shunji |
| FAMILY NAME | Mitsuyoshi |
| SIGNATURE | MITSUYOSHI S |
| AFFILIATIONS | The University of Tokyo |
| ORCID | 0000-0002-3441-3335 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Estimating Depressive Symptom Class from Voice
Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients' distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in differ…
Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach
In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive d…
Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls
A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = -0.33, p p = 0.0085, area under the curve of the receiver operating characteristic curve = 0.76)
No prominent works on this page.
Depressive Mood Assessment Method Based on Emotion Level Derived from Voice: Comparison of Voice Features of Individuals with Major Depressive Disorders and Healthy Controls
A significant negative correlation existed between the vitality extracted from the voices and HAM-D scores (r = -0.33, p p = 0.0085, area under the curve of the receiver operating characteristic curve = 0.76)
Detection of Major Depressive Disorder Based on a Combination of Voice Features: An Exploratory Approach
In general, it is common knowledge that people's feelings are reflected in their voice and facial expressions. This research work focuses on developing techniques for diagnosing depression based on acoustic properties of the voice. In this study, we developed a composite index of vocal acoustic properties that can be used for depression detection. Voice recordings were collected from patients undergoing outpatient treatment for major depressive d…
Estimating Depressive Symptom Class from Voice
Voice-based depression detection methods have been studied worldwide as an objective and easy method to detect depression. Conventional studies estimate the presence or severity of depression. However, an estimation of symptoms is a necessary technique not only to treat depression, but also to relieve patients' distress. Hence, we studied a method for clustering symptoms from HAM-D scores of depressed patients and by estimating patients in differ…
Emotion and Mood Recognition (3 works) · Mental Health Research Topics (3 works) · Psychiatry (3 works) · Psychology (3 works) · Anxiety (2 works) · Audiology (2 works) · Clinical Psychology (2 works) · Clinical Psychology (2 works) · Depression (economics (2 works) · Depressive symptoms (2 works)