The articulation of morphologically complex words

形态复杂的单词的发音

• 批准号: 274184074
• 负责人: Professor Dr. Harald Baayen
• 金额: --
• 依托单位: Arbeitsbereich Quantitative Linguistik
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/274184074?language=en
• 关键词: articulation; morphologically; complex; words

The objective of the project for the first funding period was to investigate articulatory processes encoding morphological information, and their relation to lexical proficiency. We found that suffixal morphology changes the phonetic encoding even in the stem and that speakers become more capable to do so with increased proficiency. In a joint study with project VAR, we computationally modeled durations of word-final S by means of NDL. Our findings indicate that articulatory processes are modulated by how well the relation between the phonetic signal and morphological meaning is learned by speakers.The second phase of the ART project aims to consolidate the results obtained in the first phase of the project by replicating the results obtained with EMA using ultrasound recordings and by investigating EMA recordings in the KEC corpus of spontaneous German conversations. Ultrasound, as well as the study of articulation in spontaneous speech are essential for assessing the ecological validity of the present results, which were all obtained in laboratory conditions using a slightly invasive recording technique. The project will also broaden its scope by studying articulation in a richly inflecting language, Polish, and by extending the computational modeling of speech production with NDL to, for instance, New Zealand English, as well as to homophonic exponents in German.

该项目第一个资助期的目标是研究编码形态信息的发音过程及其与词汇熟练程度的关系。我们发现，后缀形态甚至会改变词干中的语音编码，并且随着熟练程度的提高，说话者变得更有能力做到这一点。在与 VAR 项目的联合研究中，我们通过 NDL 对词尾 S 的持续时间进行了计算建模。我们的研究结果表明，发音过程是由说话者学习语音信号和形态意义之间关系的程度来调节的。ART 项目的第二阶段旨在通过使用超声记录复制 EMA 获得的结果以及调查自发德语会话 KEC 语料库中的 EMA 记录来巩固项目第一阶段获得的结果。超声波以及自发言语的发音研究对于评估当前结果的生态有效性至关重要，这些结果都是在实验室条件下使用轻微侵入性记录技术获得的。 该项目还将通过研究具有丰富屈折变化的语言（波兰语）的发音，并将 NDL 语音生成的计算模型扩展到新西兰英语以及德语的同音指数，从而扩大其范围。