<link rel="stylesheet" href="styles.cf390c6bfbe7555f.css">

學術出版;;Publications

Permanent URI for this communityhdl:11536/1

收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

Browse

Filters

1992 - 19942

Settings

🏛️國立陽明交通大學機構典藏

Author: search.filters.author.HWANG, SHSubject: search.filters.subject.NEURAL NETWORKS

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item type:Item,
    NEURAL NETWORK SYNTHESIZER OF PAUSE DURATION FOR MANDARINE TEXT-TO-SPEECH
    (1992-04-09)
    HWANG, SH
    ;
    CHEN, SH
    ;
    電信工程研究所
    ;
    電信研究中心
    ;
    Institute of Communications Engineering
    A neural network based approach of pause-duration synthesis for Mandarin text-to-speech is proposed. It uses an MLP to replace explicit synthesis rules for generating pause duration from input text. By properly training the MLP using a large set of utterances, phonological rules of producing pause duration are automatically learned. Experimental results confirmed that this is a promising approach.
  • Thumbnail Image
    Item type:Item,
    NEURAL-NETWORK-BASED F0 TEXT-TO-SPEECH SYNTHESIZER FOR MANDARINE
    (1994-12-01)
    HWANG, SH
    ;
    CHEN, SH
    ;
    電信工程研究所
    ;
    電信研究中心
    ;
    Institute of Communications Engineering
    A neural-network-based approach to synthesising F0 information for Mandarin text-to-speech is discussed. The basic idea is to use neural networks to model the relationship between linguistic features, extracted from input text and parameters representing the pitch contour of syllables. Two MLPs are used to separately synthesise the mean and shape of pitch contour, using different linguistic features. A large set of utterances is employed to train these MLPs using the well known back-propagation algorithm. Pronunciation rules for generating F0 information are automatically learned and implicitly memorised by the MLPs. In the synthesis, parameters representing the mean and shape of the pitch contour of each syllable are generated using linguistic features extracted from the given input text. Simulation results confirmed that this is a promising approach for F0 synthesis. The resulting synthesised pitch contours of syllables match well with their original counterparts. Average root mean square errors of 0.94 ms/frame and 1.00ms/frame were achieved.