Utilizing Checkpoints With Deep Neural Networks For Enhanced Speech Transcription in Neurodegenerative Diseases: A Case Study on Huntington’s Disease
by Kevin Liu
Category: Computer Science
Abstract – This paper addresses the challenges of creating a speech model for individuals with neurodegenerative diseases like Huntington's Disease (HD), who often struggle to communicate effectively due to the disease's effects on speech. The proposed approach fine-tunes a pre-trained DeepSpeech model (~43% accuracy) with HD voice data using the checkpointing process, resulting in a significantly improved speech recognition accuracy of 85%. A web application was developed to provide a modern user-friendly interface to transcribe speech in real-time. The findings highlight the potential of checkpointed speech models to improve the communication abilities of individuals with neurodegenerative diseases and help monitor disease progression.