F0 cue conflicts between tone and consonant effects

F0 提示音调和辅音效果之间的冲突

• 批准号: 22K00510
• 负责人: Perkins Jeremy
• 金额: $ 1.25万
• 依托单位: The University of Aizu
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2022
• 资助国家: 日本
• 起止时间: 2022-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22K00510/
• 关键词: peak delay; pitch accent; f0; consonant f0 effects; cue conflicts

The research was delayed by one year because of a previous project, which was itself delayed by one year due to COVID-19. The previous research project was concluded successfully, with Korean data collected and analyzed. Two papers were written from these results, both accepted for publication and presentation at ICPhS 2023 in Prague. The first paper was an acoustic analysis of the plain and tense fricatives, showing that release duration and spectral tilt differed; also, psychoacoustic roughness was analyzed, showing that it performed equally well as spectral tilt in identifying Korean tense obstruents. The second paper was written jointly with Prof. Yu Yan, a Computer Scientist whose knowledge on machine learning allowed us to use the random forest machine learning technique to test which acoustic cues were necessary and sufficient to identify the three Korean obstruent types (tense, lax and aspirated).

这项研究因为之前的一个项目推迟了一年，而该项目本身也因为新冠肺炎的原因推迟了一年。成功完成了前期研究项目，收集和分析了韩国的数据。根据这些结果撰写了两篇论文，这两篇论文都接受了在布拉格举行的ICPhS 2023上发表和提交。第一篇论文是对平缓摩擦音和紧张性摩擦音的声学分析，表明释放持续时间和频谱倾斜不同；此外，分析了心理声学粗糙度，表明它在识别朝鲜语时态障碍时表现出与频谱倾斜同样好的表现。第二篇论文是与计算机科学家严宇教授共同撰写的，他在机器学习方面的知识使我们能够使用随机森林机器学习技术来测试哪些声音提示是必要的，并且足以识别朝鲜语的三种不同类型(时态、松弛和送气)。