{"629480":{"#nid":"629480","#data":{"type":"event","title":"Ph.D. Proposal Oral Exam - Chuyao Feng","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EIntra-speaker Voice Quality Recognition for Voice Therapy\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u0026nbsp; \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Anderson, Advisor\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Rozell, Chair\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Moore\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe objective of the proposed research is to provide patients in voice therapy with automated voice quality feedback outside of the clinical room through i-vector and deep learning approaches. Voice disorders affect a large portion of the population, especially impacting heavy voice users such as teachers or call-center workers. Voice therapy requires regular voice technique practice under the guidance of a voice therapist in weekly therapy sessions. Patients commonly experience difficulty reproducing the prescribed voice technique and voice quality independently between sessions without the guidance of a voice therapist. By adapting the i-vector approach and other deep learning algorithms, the proposed work effectively examines a speaker\u0026#39;s different voice quality modes in unscripted and connected speech with high accuracy, demonstrating the potential of these methods to extend therapist judgment beyond the clinic walls.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Intra-speaker Voice Quality Recognition for Voice Therapy"}],"uid":"28475","created_gmt":"2019-12-02 15:46:11","changed_gmt":"2019-12-02 15:46:11","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-12-02T14:00:00-05:00","event_time_end":"2019-12-02T16:00:00-05:00","event_time_end_last":"2019-12-02T16:00:00-05:00","gmt_time_start":"2019-12-02 19:00:00","gmt_time_end":"2019-12-02 21:00:00","gmt_time_end_last":"2019-12-02 21:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"434371","name":"ECE Ph.D. Proposal Oral Exams"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"},{"id":"1808","name":"graduate students"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}