王士元語音學論文集（簡體書）

本文集收入王士元先生論文37篇，集中于語音學及相關領域研究，分為六個部分：語音學研究(14篇)、語音信息量研究(2篇)、音系學研究(3篇)、詞匯擴散理論(11篇)、語言演變模型研究(2篇)、語音合成和識別研究(5篇)。本文集基本涵蓋了王士元先生在語音學及相關領域的研究成果，其中，“詞匯擴散理論”是王士元先生對世界語言學理論的重要貢獻，相關論文全部收入。

王士元(William S－Y.Wang)，美國加州大學伯克利分校名譽退休教授。香港中文大學偉倫研究教授。王士元先生在語音學、語言學等多個領域都有傑出貢獻，并大力倡導跨學科研究；1960年以聲學語音學方面的論文獲得美國密歌根大學博士學位；1969年創立“詞匯擴散”理論，聞名于世界語言學界。

編者導言
Segmentation Techniques in Speech Synthesis
Segment Inventory for Speech Synthesis
Transition and Release as Perceptual Cues for Final Plosives
Frequency Studies of English Consonants
Intrinsic Cues and Consonant Perception
The Perception of Stops after s
Phonological Features of Tone
The Measurement of Functional Load
Tone 3 in Pekinese
Vowel Features, Paired Variables, and the English Vowel Shift
Perceptual Distance and the Specification of Phonological Features
Competing Changes as a Cause of Residue
Implementation of Phonological Change: The Shuang-Feng Chinese Case
Project DOC: Its Methodological Basis
Tone Change in Chao-Zhou Chinese: A Study in Lexical Diffusion
The Many Uses of F0
Why and How do We Study the Sounds of Speech?
Sound Change: Actuation and Implementation
Language Change
Perception of Sentence Boundaries With and Without Semantic Information
Psychophysical Pitch Biases Related to Vowel Quality, Intensity Difference, and Sequential Order
Use of Optical Distance Sensing to Track Tongue Motion
Language Change: A Lexical Perspective
Variation and Selection in Language Change
聲調感知問題
A Note on Tone Development
Middle Chinese Tones in Modern Dialects
Closure Duration in the Classification of Stops: A Statistical Analysis
Bidirectional Diffusion in Sound Change
吳語濁塞音的研究——統計上的分析和理論上的考慮
Snowball Effect in Lexical Diffusion: The Development of-s in the
Third Person Singular Present Indicative in English
Performance of Mandarin Connected Digit Recognizer with Word Duration Modeling
Optimization Models of Sound Systems Using Genetic Algorithms
Computational Studies of Language Evolution
An Innovative Prosody Modeling Method for Chinese Speech Recognition
Tone Recognition of Continuous Cantonese Speech Based on Support Vector Machines
宏觀語音學