The benefits of acoustic perceptual information for speech processing systems
He, Di
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HE-DISSERTATION-2019.pdf
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https://hdl.handle.net/2142/104888
Description
Title
The benefits of acoustic perceptual information for speech processing systems
Author(s)
He, Di
Issue Date
2019-04-19
Director of Research (if dissertation) or Advisor (if thesis)
Chen, Deming
Doctoral Committee Chair(s)
Chen, Deming
Committee Member(s)
Hasegawa-Johnson, Mark
Wong, Martin
Lim, Boon Pang
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2019-08-23T20:00:08Z
Keyword(s)
ASR
AED
Acoustic Landmark
Auditory Roughness
IoT
FPGA
MTL
CTC
Abstract
The frame-synchronized framework has dominated many speech processing systems, such as ASR and AED targeting human speech activities. These systems have little consideration for the science behind speech and treat the task as a simple statistical classification. The framework also assumes each feature vector to be equally important to the task. However, through some preliminary experiments, this study has found evidence that some concepts defined in speech perception theories such as auditory roughness and acoustic landmarks can act as heuristics to these systems and benefit them in multiple ways. Findings of acoustic landmarks hint that the idea of treating each frame equally might not be optimal. In some cases, landmark information can improve system accuracy through highlighting the more significant frames, or improve the acoustic model accuracy by training through MTL. Further investigation into the topic found experimental evidence suggesting that acoustic landmark information can also benefit end-to-end acoustic models trained through CTC loss. With the help of acoustic landmarks, CTC models can converge with less training data and achieve lower error rate. For the first time, positive results were collected on a mid-size ASR corpus (WSJ) for acoustic landmarks. The results indicate that audio perception information can benefit a broad range of audio processing systems.
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HE-DISSERTATION-2019.pdf
