ClinicalTrials.gov
public full text
Public Domain
Use of Conversation and Acoustic Signals in Measuring Depression Severity
The purpose of this study is to test a new monitoring technology that uses the sound of a depressed person's speech to assess the severity of depression symptoms. The Vocal Social Signals Platform (VSSP) is software that analyzes the non-verbal characteristics of a person's speech. This study will test this software to see if it could be a useful measurement tool for assessing depression symptoms. Participation in this study requires coming to the research headquarters twice over a three-month period. The first visit is to determine eligibility. Throughout the study, participants will be connected to a telephone system five times, on which they will answer questions about their depression symptoms. After answering questions, their voice will be recorded using a structured speech sample that the participant will read out loud. The participant will also give an unstructured speech sample, which will involve describing a typical day or the last movie s/he saw. The voice samples will be analyzed and compared to the results of the depression symptom questionnaires.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Research on Voice Intelligent Monitoring Technology for Early Warning of Recurrence of Depression Disorder#1150467
- Efficacy of a Conversational AI Agent for Psychiatric Symptoms and Digital Therapeutic Alliance: A Randomized Clinical Trial.#14813
- Probability of a timely vocal response in mother-infant interaction and later psychiatric diagnosis: A case-control study.#334971
- ParaCalib: Semantically Calibrated Paralinguistic Modeling for Depression Detection#1156038
- MS Synchronous vs Asynchronous Exercise Study#1074498
Record · ID 1096090
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive