Why do human languages have homophones?

Human languages are replete with ambiguity. This is most evident in homophony––where two or more words sound the same, but carry distinct meanings. For example, the wordform “bark” can denote either the sound produced by a dog or the protective outer sheath of a tree trunk. Why would a system evolved for efficient, effective communication display rampant ambiguity? Some accounts argue that ambiguity is actually a design feature of human communication systems, allowing languages to recycle their most optimal wordforms (those which are short, frequent, and phonotactically well-formed) for multiple meanings. We test this claim by constructing five series of artificial lexica matched for the phonotactics and distribution of word lengths found in five real languages (English, German, Dutch, French, and Japanese), and comparing both the quantity and concentration of homophony across the real and artificial lexica. Surprisingly, we find that the artificial lexica exhibit higher upper-bounds on homophony than their real counterparts, and that homophony is even more likely to be found among short, phonotactically plausible wordforms in the artificial than in the real lexica. These results suggest that homophony in real languages is not directly selected for, but rather, that it emerges as a natural consequence of other features of a language. In fact, homophony may even be selected against in real languages, producing lexica that better conform to other requirements of humans who need to use them. Finally, we explore the hypothesis that this is achieved by “smoothing” out dense concentrations of homophones across lexical neighborhoods, resulting in comparatively more minimal pairs in real lexica.

Clustering coefficients of lexical neighborhoods

High neighborhood density reduces the speed and accuracy of spoken word recognition. The two studies reported here investigated whether Clustering Coefficient (CC) — a graph theoretic variable measuring the degree to which a word’s neighbors are neighbors of one another, has similar effects on spoken word recognition. In Experiment 1, we found that high CC words were identified less accurately when spectrally degraded than low CC words. In Experiment 2, using a word repetition procedure, we observed longer response latencies for high CC words compared to low CC words. Taken together, the results of both studies indicate that higher CC leads to slower and less accurate spoken word recognition. The results are discussed in terms of activation-plus-competition models of spoken word recognition.

Lexical Neighborhoods and the Word-Form Representations of 14-Month-Olds

The degree to which infants represent phonetic detail in words has been a source of controversy in phonology and developmental psychology. One prominent hypothesis holds that infants store words in a vague or inaccurate form until the learning of similar-sounding neighbors forces attention to subtle phonetic distinctions. In the experiment reported here, we used a visual fixation task to assess word recognition. We present the first evidence indicating that, in fact, the lexical representations of 14- and 15-month-olds are encoded in fine detail, even when this detail is not functionally necessary for distinguishing similar words in the infant's vocabulary. Exposure to words is sufficient for well-specified lexical representations, even well before the vocabulary spurt. These results suggest developmental continuity in infants' representations of speech: As infants begin to build a vocabulary and learn word meanings, they use the perceptual abilities previously demonstrated in tasks testing the discrimination and categorization of meaningless syllables.

An Electrophysiological Study of the Effects of Orthographic Neighborhood Size on Printed Word Perception

In two experiments participants read words and pseudo-words that belonged to either large or small lexical neighborhoods while event-related brain potentials (ERPs) were recorded from their scalps. In Experiment 1, participants made speeded lexical decisions to all items, while in Experiment 2 they engaged in a go/no-go semantic categorization task in which the critical items did not require an overt behavioral response. In both experiments, words and pseudo-words produced a consistent pattern of ERP effects: items with many lexical neighbors (large neighborhoods) generated larger N400s than similar items with relatively fewer lexical neighbors (small neighborhoods). Reaction time (RT, Experiment 1), on the other hand, showed a different pattern consistent with previous behavioral studies. While words tended to produce a facilitation in RT for larger neighborhoods, pseudowords produced an inhibition effect. The findings are discussed in terms of recent theories of word recognition and the functional significance of the N400.