000042382 001__ 42382
000042382 005__ 20240124114341.0
000042382 0247_ $$2doi$$a10.6083/bpxhc42382
000042382 037__ $$aETD
000042382 041__ $$aeng
000042382 245__ $$aAutomatic speech recognition for small data and its application on cognitive assessment
000042382 260__ $$bOregon Health and Science University
000042382 269__ $$a2023-12-15
000042382 336__ $$aAbstract
000042382 502__ $$bPh.D.
000042382 502__ $$gComputer Science and Engineering
000042382 520__ $$aAutomatic speech recognition (ASR) is an essential component for building automatic cognitive assessment systems designed to monitor older adults' cognitive status. While, in the ASR field, remarkable achievements have been reported on publicly available academic datasets, two under-explored problems are important to building automatic cognitive assessment systems: ASRs' performance on aging voice and accuracy in transcribing keywords. Both problems are important to deliver high-quality transcriptions for assessment purposes. In this dissertation, we focus on developing transfer learning techniques/methods to build ASRs that perform well on older adults with possible cognitive impairment. Firstly, we present a transfer learning technique to improve an open-source ASR's performance on older adults (80+ years old) with limited data (i.e., about 10 hours of audio recordings). We demonstrate that the aging voice dramatically impacts an ASR's performance and that adapting the ASR with older adults' recording data through fine-tuning can improve the performance. We propose a transfer learning technique that utilizes intermediate outputs to increase the fine-tuning efficiency with limited training data. This technique achieves better performance than the standard fine-tuning.
000042382 540__ $$fCC BY
000042382 542__ $$fIn copyright - single owner
000042382 650__ $$aAged$$014351
000042382 650__ $$aCognitive Dysfunction$$039814
000042382 653__ $$1Automatic speech recognition
000042382 6531_ $$asmall data
000042382 6531_ $$aautomatic speech recognition
000042382 691__ $$aSchool of Medicine$$041369
000042382 692__ $$aCenter for Spoken Language Understanding$$041388
000042382 7001_ $$aChen, Liu$$uUniversity of Oregon Health Sciences Center$$041361$$10000-0003-3366-0294
000042382 8564_ $$95eee27ef-da56-4b0a-8410-455ebc808813$$s14021071$$uhttps://digitalcollections.ohsu.edu/record/42382/files/Chen.Liu.2023.pdf
000042382 909CO $$ooai:digitalcollections.ohsu.edu:42382$$pstudent-work
000042382 980__ $$aTheses and Dissertations
000042382 981__ $$aPublished$$b2023-12-15