母語與非母語英語之韻律模型建立

Abstract

本論文提出一個以音節為單位的韻律模型，其中包含了音節時間模型以及音節基頻軌跡模型。本論文考慮了若干會對這兩項韻律參數影響的因子，其中包括了重音類型、詞長、鄰近的停頓類型、音節組成的因素及韻律狀態等等。本論文使用一個疊代式的訓練法來建立此模型，並使用包含了母語與非母語英文語料的TWNAESOP語料庫。實驗數據顯示此模型能夠有效的建立起英語的韻律模型，與許多前人的研究結果符合；並且透過探討母語與非母語語者參數間的差別，我們得以從數據上得知兩者間韻律上的差異。

In this thesis, a statistical prosody modeling approach for L1 and L2 English speeches is proposed. The study focuses on the modeling of two prosodic-acoustic features: syllable duration and log-pitch contour. Several major affecting factors (AFs) that influence the variations of these two features are considered. They include lexical stress, word length, nearby break type, phonemic constituent of syllable, and prosodic state. A sequential optimization procedure is adopted to automatically train the two models from the TWNAESOP corpus recorded in Taiwan. The corpus contained both L1 and L2 English speeches. Experimental results showed that most AFs estimated agreed well with our prior linguistic knowledge. The differences in the prosody of L1 and L2 speeches were explored.