Vocal Lens: Integrating Speech Biomarkers for Advanced Health Diagnostics
Explore the frontier of medical technology by developing a cutting-edge system to analyze speech biomarkers and revolutionize diagnostic practices.
Project description
In this project, our objective is to develop a prototype for an end-to-end system dedicated to speech biomarker analysis. Human speech encompasses a wealth of clues and information that can indicate various health conditions, including neurological (e.g., PD and ASD), mental (Anxiety and Depression), and developmental disorders (speech impairment). Our team aims to delve into the multifaceted layers of information embedded within human speech, focusing on both physical and semantic features.
The project encompasses several key technical domains: signal processing, machine learning, mobile computing, and human-computer interaction. We will integrate these disciplines to create a comprehensive interdisciplinary application with significant medical relevance. Our goal is to leverage advanced technology to enhance diagnostic methodologies and improve healthcare outcomes through innovative speech analysis techniques.
Project outcome
1) Development of a Prototype System: Successfully build an integrated prototype that analyzes speech biomarkers using advanced signal processing and machine learning techniques.
2) Interdisciplinary Collaboration: Foster collaboration across fields such as computer science, medicine, and engineering, culminating in a comprehensive approach to health diagnostics.
3) Publication and Dissemination: Aim to publish findings in peer-reviewed journals and present at conferences, contributing valuable knowledge to the scientific and medical communities.
4) Educational Impact: Provide students and researchers with hands-on experience in applying cutting-edge technology to real-world medical challenges, enhancing their skills and professional growth.
Project details
| Length of commitment | Year-long (10-12 months) |
| Start time | Anytime |
| In-person, remote, or hybrid? | Hybrid Project |
| Level of collaboration | Small group project (2-3 students) |
| Benefits | Academic credit Stipend |
| Who is eligible | All undergraduate students |
Core partners
- UB medical school
Project mentor
Wenyao Xu
Professor
Computer Science and Engineering
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase.
Please read and get familier with these two articles relating to the project.
VocalLensIntegratingSpeechBiomarkersforAdvancedHealthDiagnostics_80230066_adrd.pdf | Powered by Box
Keywords
Machine Learning; App Development