The visome: Using cognitive networks to examine lip-reading errors in English words

Network science was used to examine how English words look rather than sound when spoken. Measures of the visome (network of visual word representations) were compared to a phonological network at the macro- (whole network), meso- (subsets of nodes), and micro-levels (individual nodes) to determine how the structure of the visome influences lipreading performance. Conventional psycholinguistic measures and network structure measures were further examined in two databases of lipreading errors. Lipreading errors were higher in frequency of occurrence than the target words. Target words had uniqueness points that occurred after the end of the word (indicating that they are embedded in other words in the visome). Words varied in the number of viseme twins they have (i.e., words that look the same when spoken), and words with many twins are lipread less accurately than words with fewer twins. Words with many viseme neighbors (the word is related to another word by the addition, deletion, or substitution of a viseme) were also lipread less accurately than words with fewer viseme neighbors. Errors tended to reside in the same community as the target word instead of in a different community. Network analysis may be useful for reviving and advancing research on lipreading.