Parallel vs Serial Issues in Reading Aloud: Evidence for Parallel Processing from a Computational Model of Japanese Kanji & Kana Nonword Reading

Parallel vs Serial Issues in Reading Aloud: Evidence for Parallel Processing from a Computational Model of Japanese Kanji & Kana Nonword Reading Taiji Ueno 1,2 (taijiueno7@gmail.com) Kenji Ikeda 2,3 (ikeda.kenji@f.mbox.nagoya-u.ac.jp) Yuichi Ito 2,3 (ito.yuichi@nagoya-u.jp) Shinji Kitagami 3 (kitagami@cc.nagoya-u.ac.jp) Jun Kawaguchi 3 (kawaguchijun@nagoya-u.jp) 1. Department of Psychology, University. of York, Heslington, York, YO10 5DD, UK. 2. Japan Society for the Promotion of Science; 3. Graduate School of Environmental Studies, Nagoya University, Nagoya, 4648601, JAPAN. Abstract Lower nonword reading performance in the old version of parallel-distributed processing models in English was taken as evidence for the necessity of sequential components in reading aloud, but the later updates have resolved this issue without discarding the parallel processing principle. A model’s validity can be tested by cross-script extensions. On this point, an extension to Japanese kanji reading has posed a question. Specifically, the latest Japanese connectionist model has incorporated a sequential component in order to improve kanji nonword reading performance. The present study, however, proposed an alternative, fully parallel-distributed processing model to map distributed kanji and kana visual representations to phonemic/moraic representations, with satisfactory nonword reading performance. First cross- linguistic evidence from Japanese is provided to support a single-mechanism theory that postulates parallel-processing for both words and nonwords reading. Keywords: parallel-distributed processing model; sequential processing; reading, Japanese kanji; nonword reading Introduction The processes and mechanisms for reading aloud is one of the controversial issues in cognitive science. Implemented computational models have contributed to this issue by explicitly demonstrating the mechanisms and processes that can reproduce the behavioral data (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Perry, Ziegler, & Zorzi, 2007; Plaut, McClelland, Seidenberg, & Patterson, 1996). These models differ in whether a sequential component is permitted as well as parallel processing component, mainly in order to simulate nonword reading accuracy (Besner & Smith, 1992) and the word length effect (Weekes, 1997), and so on. The present study contributes to this issue by providing the first example of a parallel-distributed processing (PDP, without a sequential component) connectionist model which can read Japanese kanji and kana words/nonwords. A historical overview of the parallel vs serial issues in English models should be helpful here. The PDP model by Seidenberg and McClelland (1989) incorporated only a single mechanism with parallel processing, and was able to read both regular (e.g., mint) and irregular (i.e., pint) words. However, this model (hereafter, SM89) was unable to read nonwords (i.e., untrained input pattern) as satisfactorily as humans (Glushko, 1979). Advocates of dual-route models argued that SM89 was only an approximation of a lexical look-up process, and this was taken as evidence for the necessity of sequential components (Coltheart et al., 2001). Specifically, they expected that sequentially applying a grapheme-phoneme correspondent rule per a grapheme would allow a model to pronounce a nonword satisfactorily. In contrast, Plaut et al. (Plaut et al., 1996) explained it was only due to the size of the training set and/or to the input coding schemes. After sorting these issues out, Plaut et al. (hereafter, PMSP96) successfully simulated nonword reading performance without a sequential component. Interestingly, the connectionist models for Japanese kanji reading went part of the same way as English, but arrived at the opposite end. It is widely accepted that a cross-script extension is a useful paradigm to glean further evidence for the validity of computational models (Perry et al., 2007). Given the success of PMSP96, it was natural that one of these authors, Patterson and her Japanese colleagues embarked on a Japanese PDP project. The outcome of their initial attempt was successful and similar to the situation of SM89, such that the model was able to read both Japanese kanji consistent/regular words (later in details for the operational definition) and irregular words within a single mechanism (Ijuin, Fushimi, Patterson, & Tatsumi, 1999). However, this model was unable to read kanji nonwords (2- kanji compounds, but the combination of these 2 kanji characters does not exist in real Japanese) as correctly as humans (Fushimi, Ijuin, Patterson, & Tatsumi, 1999). Given the history of English models, they naturally expected that poor nonword reading would be attributed to extrinsic factors such as training corpus and coding schemes, rather than intrinsic factors such as its lack of indispensable mechanisms. However, the follow-up studies conducted by Japanese researchers in this group (Ijuin, Fushimi, & Tatsumi, 2001, 2002) have actually reached the different conclusion. Specifically, Ijuin et al. (2001) explicitly mentioned as follows (translated into English by us):