From Words to Well-being: Analyzing Systems for Depression Detection through Speech

Abstract

The study From Words to Well-being: Analyzing Systems for Depression Detection through Speech explores the innovative intersection of linguistics, technology, and mental health to develop effective tools for identifying depression through speech analysis. As depression continues to pose significant global health challenges, early detection and intervention become crucial. This research evaluates various speech-based systems, leveraging advancements in natural language processing (NLP) and machine learning (ML) to identify linguistic and acoustic markers indicative of depressive states. By analyzing vocal characteristics such as tone, pitch, and speech patterns, alongside textual content, these systems aim to offer non-invasive, real-time insights into an individual's mental health. The study compares the efficacy, accuracy, and practicality of different approaches, highlighting their potential for integration into clinical practices and everyday applications. The findings underscore the promise of speech analysis as a complementary tool in mental health diagnostics, potentially revolutionizing how depression is detected and managed, thereby contributing to improved well-being and quality of life. From Words to Well-being: Analyzing Systems for Depression Detection Through Speech investigates the potential of speech analysis as a tool for early detection of depression. This research examines various speech-based systems that utilize advancements in natural language processing (NLP) and machine learning (ML) to identify markers of depression in both the content and acoustic properties of speech. By assessing features such as tone, pitch, speech patterns, and linguistic content, these systems aim to provide non-invasive and real-time insights into an individual's mental health. The study evaluates the effectiveness, accuracy, and feasibility of different approaches, highlighting their potential applications in clinical settings and everyday life. The findings demonstrate the promise of integrating speech analysis into mental health diagnostics, offering a novel method for detecting and managing depression, ultimately contributing to improved overall well-being.