Tóth Máté Attila, García Lecumberri María Luisa, Tang Yan, Cooke Martin
Language and Speech Laboratory, Universidad del País Vasco, 01006 Vitoria, Spain
School of Computing, Science and Engineering, University of Salford, Salford, United Kingdom
J Acoust Soc Am. 2015 Feb;137(2):EL184-9. doi: 10.1121/1.4905877.
Word misperceptions are valuable in designing and evaluating detailed computational models of speech perception, especially when a number of listeners agree on the misperceived word. The current paper describes the elicitation of a corpus of Spanish word misperceptions induced by different types of noise. Stimuli were presented using an adaptive procedure designed to promote the rapid discovery of misperceptions. The final corpus contains 3235 misperceptions along with speech and masker waveforms, permitting further experimental and modeling studies into the origin of each misperception. The corpus is available online as an open resource.
单词误听在设计和评估语音感知的详细计算模型方面很有价值，尤其是当许多听众对误听的单词达成一致时。本文描述了由不同类型噪声引发的西班牙语单词误听语料库的引出过程。使用旨在促进快速发现误听的自适应程序呈现刺激。最终语料库包含3235个误听以及语音和掩蔽波形，允许对每个误听的起源进行进一步的实验和建模研究。该语料库作为开放资源在线提供。
