Real Words, Possible Words, and New Words

Real Words, Possible Words, and New Words Janet B. Pierrehumbert (jbp@northwestern.edu) Linguistics Department Northwestern University 2016 Sheridan Rd. Evanston IL 60208 Keywords: lexicon; phonotactics; morphology; nonwords; word frequency; word formation Introduction Phonologists and psycholinguists draw a three-way distinc- tion amongst real words, possible words, and impossible words.The distinction between real words and possible words provides the foundation for lexical decision experiments. The distinction between possible words and impossible words re- veals implicit cognitive generalizations about words in a lan- guage, and thereby contributes to the understanding of lan- guage acquisition and processing. Left to the side in this vast body of theory and experimental results is a real understand- ing of new words. Is a new word just a new random selection from the possible words? No. First of all, some possible words are more possible than others. Second, there’s an im- portant distinction between the creation of a new word, and its adoption by the linguistic community. The creation of a new word is a manifestation of an individual person’s cogni- tive system. But to be widely adopted, it must successfully compete with other words to be used in discourse. In this paper, I review a series of results on how and why some possible words are more possible than others. Then, I will introduce work in progress that looks at the interaction of social and cognitive factors in processing new words. Phonotactics The phonology of a language is a grammar for its sound struc- ture. The simplest type of grammar is a diphone grammar. Many studies have revealed gradient effects of diphone statis- tics in predicting the inventory of word types and the extent to which nonwords are judged to be well-formed. These in- clude Frisch, Large, and Pisoni (2010); Hay, Pierrehumbert, and Beckman (2004). For English, diphone statistics alone can provide a powerful method for bootstrapping the lexicon from continuous speech (Daland & Pierrehumbert, 2011). In a widely used algorithm for generating nonwords, diphone statistics are the only treatment of the phonological grammar per se (Rastle, Harrington, & Coltheart, 2002). However, constraints at larger time-scales are also found in phonology. These, too, make gradient and cumulative con- tributions to the well-formedness of nonwords. To capture effects of syllable structure, it is necessary to use triphone statistics and/or an explicit hierarchical structure (Coleman & Pierrehumbert, 1997; Hay et al., 2004; Pierrehumbert, 1994). Stress modulates the likelihood of different phones at larger time-scales (Coleman & Pierrehumbert, 1997). Cross- linguistically, a common constraint mitigates against se- quences of consonants with the same place of articulation, re- gardless of the intervening vowels. In Arabic, this constraint displays a cumulative interaction between the similarity of the consonants and their distance (Frisch, Pierrehumbert, & Broe, 2004). In general, local constraints can make detailed reference to segmental features, whereas constraints involving long spans of phonemes tend to refer to more general classes. This gen- eralization follows from learnability considerations. Form- ing a statistical generalization requires a big enough sam- ple of word types to distinguish a significant pattern from a simpler null hypothesis about the grammar (Pierrehumbert, 2001). The means by which the cognitive system combines precise local statistical constraints with broad non-local sta- tistical constraints is not yet well understood. Morphology Morphology is the theory of how words are made from mean- ingful parts. Several studies just cited involve morphologi- cal structure as well as phonological structure. In Hay et al. (2004), diphone statistics of bisyllabic nonwords predicted well-formedness judgments, but only given the best morpho- logical parse of the nonword. In Frisch et al. (2010), the Arabic statistical patterns pertain to verbal roots, which are a morphological abstraction from the surface forms. The sur- face forms include obvious violations of the constraints, due to the operation of the non-concatenative Arabic word forma- tion system. New words are judged to be much better if they have a valid morphological analysis. In fact, productive morphology is the dominant source of new words. In languages such as Turkish and Finnish, the morphology is so productive that the lexicon cannot be construed as a stable, shared, inventory of words (Creutz & Lagus, 2007), and morpheme-based systems perform better than word-based systems in speech engineer- ing (Hirsim¨aki, Pylkk¨onen, & Kurimo, 2009). Learning mor- phology involves learning statistics about relations of words to each other (Pierrehumbert, 2003, 2006). The best known predictor of the productivity of a morphological pattern is the number of word types that exhibit the pattern, and the trans- parency with which they exhibit it, including both semantic and phonological transparency (Racz, Pierrehumbert, Hay, & Papp, in press). Exploiting the fact that meaningful units are found in more different combinations than arbitrary units, un- supervised learning algorithms that lack any overt semantics perform remarkably well (Creutz & Lagus, 2007).