计算机科学
语音识别
词(群论)
网络科学
人工智能
复杂网络
自然语言处理
语言学
万维网
哲学
作者
Michael S. Vitevitch,David B. Pisoni,Lauren E Soehlke,Tyler Foster
出处
期刊:Ear and Hearing
日期:2023-06-15
卷期号:45 (1): 1-9
被引量:1
标识
DOI:10.1097/aud.0000000000001395
摘要
In this Point of View, we review a number of recent discoveries from the emerging, interdisciplinary field of Network Science , which uses graph theoretic techniques to understand complex systems. In the network science approach, nodes represent entities in a system, and connections are placed between nodes that are related to each other to form a web-like network . We discuss several studies that demonstrate how the micro-, meso-, and macro-level structure of a network of phonological word-forms influence spoken word recognition in listeners with normal hearing and in listeners with hearing loss. Given the discoveries made possible by this new approach and the influence of several complex network measures on spoken word recognition performance we argue that speech recognition measures—originally developed in the late 1940s and routinely used in clinical audiometry—should be revised to reflect our current understanding of spoken word recognition. We also discuss other ways in which the tools of network science can be used in Speech and Hearing Sciences and Audiology more broadly.
科研通智能强力驱动
Strongly Powered by AbleSci AI