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postgraduate thesis: Application of implicit learning paradigm in voice motor learning

TitleApplication of implicit learning paradigm in voice motor learning
Authors
Advisors
Issue Date2018
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Omuro, S. [大室貞宏]. (2018). Application of implicit learning paradigm in voice motor learning. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractThe production of sufficient speech intensity is a prerequisite for living a normal life. Mixed findings regarding the efficacy of different speech intensity interventions have been reported. Therefore, identification of optimal intervention paradigms for patients with low speech intensity is needed. One approach to this issue involves the application of principles of limb motor learning to the speech motor domain. Thus far, only a handful of studies utilising these principles of motor learning in the speech domain have been published, generally demonstrating promising results. This thesis investigates the effects of two motor learning paradigms, error-reduced learning and subliminal feedback learning, in the area of voice motor learning. Additionally, we investigate whether long-term retention of voice motor learning is present after use of these paradigms. Chapter 2 identified the Just Noticeable Differences (JNDs) for discriminating subtle differences in a visual task associated with speech intensity. The JNDs were then used to investigate the effects of subliminal feedback learning in a speech intensity task in Chapter 3. Results indicated that it is possible to trigger adaptations of an individual’s motor behaviour (i.e., speech intensity) by subtle manipulations of the visual stimuli. Chapter 4, 5 and 6 investigated the effects of an error-reduced learning paradigm on voice motor learning. The experiments tested the efficacy of error-reduced training protocols for speech intensity control. The final chapter compared a combined JND error-reduced learning paradigm with a learning condition similar to a conventional voice treatment for enhancing speech intensity level. In general, results demonstrated a significant increase in speech intensity. Unfortunately, significant long-term effects were not found and speech intensity returned back to baseline levels after 3 days. This thesis yields insights into the potentials of two implicit motor learning paradigms in the domain of voice motor learning. Directions for further research are indicated to enhance the retention of the learnt task.
DegreeDoctor of Philosophy
SubjectImplicit learning
Voice
Motor learning
Dept/ProgramSpeech and Hearing Sciences
Persistent Identifierhttp://hdl.handle.net/10722/268412

 

DC FieldValueLanguage
dc.contributor.advisorMa, EPM-
dc.contributor.advisorMasters, RSW-
dc.contributor.authorOmuro, Sadahiro-
dc.contributor.author大室貞宏-
dc.date.accessioned2019-03-21T01:40:18Z-
dc.date.available2019-03-21T01:40:18Z-
dc.date.issued2018-
dc.identifier.citationOmuro, S. [大室貞宏]. (2018). Application of implicit learning paradigm in voice motor learning. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/268412-
dc.description.abstractThe production of sufficient speech intensity is a prerequisite for living a normal life. Mixed findings regarding the efficacy of different speech intensity interventions have been reported. Therefore, identification of optimal intervention paradigms for patients with low speech intensity is needed. One approach to this issue involves the application of principles of limb motor learning to the speech motor domain. Thus far, only a handful of studies utilising these principles of motor learning in the speech domain have been published, generally demonstrating promising results. This thesis investigates the effects of two motor learning paradigms, error-reduced learning and subliminal feedback learning, in the area of voice motor learning. Additionally, we investigate whether long-term retention of voice motor learning is present after use of these paradigms. Chapter 2 identified the Just Noticeable Differences (JNDs) for discriminating subtle differences in a visual task associated with speech intensity. The JNDs were then used to investigate the effects of subliminal feedback learning in a speech intensity task in Chapter 3. Results indicated that it is possible to trigger adaptations of an individual’s motor behaviour (i.e., speech intensity) by subtle manipulations of the visual stimuli. Chapter 4, 5 and 6 investigated the effects of an error-reduced learning paradigm on voice motor learning. The experiments tested the efficacy of error-reduced training protocols for speech intensity control. The final chapter compared a combined JND error-reduced learning paradigm with a learning condition similar to a conventional voice treatment for enhancing speech intensity level. In general, results demonstrated a significant increase in speech intensity. Unfortunately, significant long-term effects were not found and speech intensity returned back to baseline levels after 3 days. This thesis yields insights into the potentials of two implicit motor learning paradigms in the domain of voice motor learning. Directions for further research are indicated to enhance the retention of the learnt task.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshImplicit learning-
dc.subject.lcshVoice-
dc.subject.lcshMotor learning-
dc.titleApplication of implicit learning paradigm in voice motor learning-
dc.typePG_Thesis-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineSpeech and Hearing Sciences-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_991044091306703414-
dc.date.hkucongregation2019-
dc.identifier.mmsid991044091306703414-

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