The Chinese Route Argument: Predicting the Longitude and Latitude of Cities in China and the Middle East Using Statistical Linguistic Frequencies.

The Chinese Route Argument: Predicting the Longitude and Latitude of Cities in China and the Middle East Using Statistical Linguistic Frequencies Max M. Louwerse (mlouwerse@memphis.edu) Department of Psychology / Institute for Intelligent Systems, University of Memphis 365 Innovation Drive, Memphis, TN 38152 USA Sterling Hutchinson (schtchns@memphis.edu) Department of Psychology / Institute for Intelligent Systems, University of Memphis 365 Innovation Drive, Memphis, TN 38152 USA Zhiqiang Cai (zcai@memphis.edu) Institute for Intelligent Systems, University of Memphis 365 Innovation Drive, Memphis, TN 38152 USA Abstract Many cognitive scientists place a strong theoretical emphasis upon how symbols become grounded (Barsalou, 1999; Glenberg, 1997; Harnad, 1990; Pulvermuller, 1999; Searle, 1980). These researchers express an increased concern regarding symbolic representations of meaning, and do not endorse analogies between computational and human approaches towards deriving meaning (Pecher & Zwaan, 2005; Semin & Smith, 2008). Embodiment theorists state that meaning cannot lie within arbitrary amodal symbol systems; instead, meaning extraction continuously involves the activation of perceptual experiences. Indeed, learning Chinese as a monolingual English speaker with only a Chinese-Chinese dictionary would lead to a symbolic merry-go-round (Harnard, Computationally translating symbols into other symbols is however what computer models do, and computational simulations are therefore fundamentally different from human cognitive processes (Glenberg & Robertson, 2001). One computational model of meaning extraction that is frequently used is latent semantic analysis (LSA; Landauer, McNamara, Dennis, & Kintsch, 2007). LSA establishes meaning representation based on co-occurrences of words in same contexts. The words Beijing and Shanghai therefore have a high similarity in (computational) meaning. However, because Beijing is not grounded in perceptual experiences, it does not have human-like meaning (Glenberg & Robertson, 2001). For instance, when humans process the word Beijing they might see a map of China and are able to ‘see’ the city in the northeast of the country. Estimating the location of Beijing using a corpus-based computational model would seem impossible, because of the Chinese Room argument. If the location of Beijing were to be estimated using amodal symbol systems, explicit spatial cues, such as prepositions and cardinal directions are needed (e.g., Beijing is north of Shanghai). Such spatial cues would lead to a combinatorial explosion with each city being added (Beijing is north of Shanghai, Chongqing is southwest of Beijing, Chongqing is west of Shanghai, etc.). The Chinese Room argument describes a thought experiment that suggests that for symbols to become meaningful, they must be grounded in perceptual experiences. Embodied cognition theorists frequently use this argument to claim that cognition requires perceptual simulation. We shed light on the symbol grounding problem by arguing that the structure of natural language provides language users with cues that allow them to bootstrap meaning from non-grounded symbolic co- occurrences, such that the statistical linguistic structure can bootstrap meaning with minimal grounding. Two studies show that co-occurrences of both Chinese and Arabic city names can reliably predict their longitude and latitude in China and in the Middle East. Using the statistical linguistic technique Latent Semantic Analysis, similarity ratings were obtained for Chinese city names (Study 1) and for Arabic city names (Study 2). Multidimensional scaling (MDS) coordinates of these similarity ratings correlated with the actual longitude and latitude of these cities, showing that cities that are located together share similar semantic contexts. These results suggest that the Chinese Room argument might be substituted with a Chinese Route argument: statistical linguistic frequencies of word co- occurrences provide language users with implicit cues about how to form perceptual representations. Keywords: symbol grounding problem; geography; spatial cognition; latent semantic analysis; symbolic cognition; embodied cognition Chinese Room Argument A monolingual English speaker sits in a room; all he has is a Chinese newspaper. Even though there is a wealth of Chinese language at his disposal, few would argue that he understands Chinese. In fact, even if he can successfully find a specific Chinese word, e.g., 上海, in his newspaper, and the collocations of that word, say, 北京, and 香港, there is little evidence he knows the meaning of those words. This Chinese room argument has been used by Searle (1980) to illustrate the symbol grounding problem in cognition (Harnad, 1990), which questions a computational account of meaning acquisition.