Harvard Catalyst Profiles

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Jordan R Green, Ph.D.

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Available: 01/14/24, Expires: 12/13/24

Project Overview: This research project is dedicated to enhancing the accuracy and efficiency of Automatic Speech Recognition (ASR) systems in assessing speech impairments associated with Amyotrophic Lateral Sclerosis (ALS). The project aims to analyze speech recordings from over 100 individuals with ALS-induced speech impairments. The project seeks to improve the ASR technology's adaptability and responsiveness to speech variations caused by ALS by conducting comprehensive acoustic analyses and comparing outputs from various ASR models. Objectives: *To collect and analyze a large dataset of speech recordings from ALS patients. *To perform detailed acoustic analyses of these recordings, focusing on characteristics altered by ALS. *To compare the performance of different ASR models in accurately transcribing ALS-affected speech. *To develop recommendations for optimizing ASR systems for use with speech-impaired individuals. Duties of Undergraduate Research Trainee: *Data Collection and Management: Assist in the collection and organization of speech recordings. This involves ensuring the quality and consistency of the data collected and maintaining a well-organized database. *Acoustic Analysis: Support the acoustic analysis process using specialized software tools. This includes identifying and categorizing speech features affected by ALS. *ASR Model Testing: Participate in the testing and evaluation of various ASR models. This involves running speech samples through these models and documenting their performance in terms of accuracy and efficiency. *Data Analysis and Python Programming: Utilize Python programming skills for data analysis. This involves writing scripts to automate parts of the analysis, such as feature extraction or comparison of ASR outputs. *Literature Review and Documentation: Conduct a thorough literature review on ALS and its impact on speech, as well as current advancements in ASR technology. Document findings and progress in a clear and organized manner. *Team Collaboration: Work collaboratively with the research team, attending meetings, and contributing to discussions on project development and problem-solving strategies. Preferred Skills: *Proficiency in Python programming, particularly in data handling and analysis. *Strong organizational skills and attention to detail. *Ability to work collaboratively in a research team environment. *Eagerness to learn and contribute to groundbreaking research in speech technology and neurological disorders.

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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.