LDR | | 02410nam u200433 4500 |
001 | | 000000420060 |
005 | | 20190215164155 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438175389 |
035 | |
▼a (MiAaPQ)AAI10827202 |
035 | |
▼a (MiAaPQ)washington:18639 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 401 |
100 | 1 |
▼a Panfili, Laura Maggia. |
245 | 10 |
▼a Cross-Linguistic Acoustic Characteristics of Phonation: A Machine Learning Approach. |
260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2018. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
300 | |
▼a 360 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: A. |
500 | |
▼a Adviser: Richard Wright. |
502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2018. |
520 | |
▼a Phonation, the process of producing a quasi-periodic sound wave through vocal fold vibration, plays different roles in different languages. Phonation types, or voice qualities, are produced by adjusting the length, thickness, and separation of t |
520 | |
▼a This study examines phonation in six languages from four families: English, Gujarati, Hmong, Mandarin, Mazatec, and Zapotec. These languages use phonation in a variety of ways, including contrastively, alongside tones, sociolinguistically, allop |
520 | |
▼a Machine learning was also used to fine tune a classifier for English phonation types. Unlike other voice quality classifiers, this study focuses on just English and on the three-way breathy vs. modal vs. creaky contrast, rather than on a binary |
520 | |
▼a This dissertation demonstrates that machine learning is a powerful tool for the study of phonation. It illuminates some of the previously unexamined similarities and differences between phonation types in different languages, and introduces a ne |
590 | |
▼a School code: 0250. |
650 | 4 |
▼a Linguistics. |
650 | 4 |
▼a Artificial intelligence. |
690 | |
▼a 0290 |
690 | |
▼a 0800 |
710 | 20 |
▼a University of Washington.
▼b Linguistics. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12A(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0250 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998997
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a ***1012033 |