Several databases of written language exist in Spanish that manage important information on the lexical and sublexical characteristics of words. However, there is no database with information on the productivity and frequency of use of derivational suffixes: sublexical units with an essential role in the formation of orthographic representations and lexical access. This work examines these two measures, known as type and token frequencies, for a series of 50 derivational suffixes and their corresponding orthographic endings. Derivational suffixes are differentiated from orthographic endings by eliminating pseudoaffixed words from the list of orthographic endings (cerveza [beer] is a simple word despite its ending in -eza). We provide separate data for child and adult populations, using two databases commonly accessed by psycholinguists conducting research in Spanish. We describe the filtering process used to obtain descriptive data that will provide information for future research on token and type frequencies of morphemes. This database is an important development for researchers focusing on the role of morphology in lexical acquisition and access.

Language-specific orthography (i.e., letters or bigrams that exist in only one language) is known to facilitate language membership recognition. Yet the contribution of continuous sublexical and lexical statistics to language membership decisions during visual word processing is unknown. Here, we used pseudo-words to investigate whether continuous sublexical and lexical statistics bias explicit language decisions (Experiment 1) and language attribution during naming (Experiment 2). We also asked whether continuous statistics would have an effect in the presence of orthographic markers. Language attribution in both experiments was influenced by lexical neighborhood size differences between languages, even in presence of orthographic markers. Sublexical frequencies of occurrence affected reaction times only for unmarked pseudo-words in both experiments, with greater effects in naming. Our results indicate that bilinguals rely on continuous language-specific statistics at sublexical and lexical levels to infer language membership. Implications are discussed with respect to models of bilingual visual word recognition.