In this fascinating paper, researchers use deep learning to explore the concept of non-arbitrariness in language. Using different sequence-processing neural networks, they assess the prevalence of non-arbitrary phonological patterns in various languages. Through a series of experiments, they train the models to associate the sounds of words with their sensory, semantic, and word-class representations. The exciting part is that these trained models are then tested on completely new instances in languages from different language families – and they perform remarkably well! This suggests that there are universal cues in the phonological structure of words that provide insights into their meaning and syntax, regardless of the language they belong to. This study not only sheds light on the universality of language but also demonstrates the power of deep learning in uncovering hidden linguistic patterns. For more details on their methodology and findings, check out the full article!
Abstract
The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set of languages to associate the phonetic vectorization of a set of words to their sensory (Experiment 1), semantic (Experiment 2), and word-class representations (Experiment 3). The models are then tested, without further training, in a set of novel instances in a language belonging to a different language family, and their performance is compared with a randomized baseline. We show that the three cross-domain mappings can be successfully transferred across languages and language families, suggesting that the phonological structure of the lexicon is pervaded with language-invariant cues about the words’ meaning and their syntactic classes.
Dr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped potential of the human mind, Dr. Lowemann has dedicated his career to pushing the boundaries of human capabilities and understanding.
Armed with a Master of Science degree and a Ph.D. in his field, Dr. Lowemann has consistently been at the forefront of research and innovation, delving into ways to optimize human performance, cognition, and overall well-being. His work at the Institute revolves around a profound commitment to harnessing cutting-edge science and technology to help individuals lead more fulfilling and intelligent lives.
Dr. Lowemann’s influence extends to the educational platform BetterSmarter.me, where he shares his insights, findings, and personal development strategies with a broader audience. His ongoing mission is shaping the way we perceive and leverage the vast capacities of the human mind, offering invaluable contributions to society’s overall success and collective well-being.