Development and Related research of Hioliuk Hakka Input Method on Mobile Devices / 智慧手機海陸腔輸入法的研發與相關研究

碩士 / 國立聯合大學 / 資訊工程學系碩士班 / 106 / According to a survey data about the Hakka dialect made by Hakka Affairs Council in 2016, Hakka people in Taiwan has a population ratio of 19.3%, with 4.537 million people, making it the second largest cultural group in Taiwan. Coincidentally, the researcher of this thesis is a Taiwanese from Hsinchu city with a Hakka origin. Also, the Hakka accent in this area in Hsinchu is called Hioliuk accent. Thus, this thesis is based on Hioliuk accent.
The Hakka input method not only has the basic functions such as Preference, Quick-type, words- prediction, but also displays a pinyin selection on the smart phone monitor for the user to key-in the desired word and instantly provides the special Hakka characters. This input method is designed for people who do not understand Hakka language well, and allows the users to use phonetic notation (without tones) as input. After keying in, the system will check its meaning and output the Hakka characters to finally choose from.
There are 5,366 records in Hakka Single Word Pinyin database (table), 19,351 records in Hakka Word Pinyin database (table), 8,505 records in Hakka Previous and Successive Word database (table) and 1,679 records in Chinese To Hakka database (table). Speech synthesis system requires many voice files: 2,949 word files and 1,566 phrases provided by Hakka Affairs Council and Ministry of Education.
In the survey questionnaire filled-out by users, Hioliuk input method got 4.0 points on average. Chinese To Hakka input method got 4.5 points on average, Hakka Language pronunciation got 4.3 points on average. Most users in Taiwan use pinyin input method, which has the big influence on the points. In the questionnaire about voice input, users believe that this system is conducive to those people who are learning Hakka and effective for the development of e-learning.

Identiferoai:union.ndltd.org:TW/106NUUM0392002
Date January 2018
CreatorsLIU, MING-CHUN, 劉名峻
ContributorsHUANG, FENG-LONG, 黃豐隆
Source SetsNational Digital Library of Theses and Dissertations in Taiwan
Languagezh-TW
Detected LanguageEnglish
Type學位論文 ; thesis
Format52

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