Rutherford Goldstein

Insights into failed lexical retrieval from network science

Previous network analyses of the phonological lexicon (Vitevitch, 2008) observed a web-like structure that exhibited assortative mixing by degree: words with dense phonological neighborhoods tend to have as neighbors words that also have dense phonological neighborhoods, and words with sparse phonological neighborhoods tend to have as neighbors words that also have sparse phonological neighborhoods. Given the role that assortative mixing by degree plays in network resilience, we examined instances of real and simulated lexical retrieval failures in computer simulations, analysis of a slips-of-the-ear corpus, and three psycholinguistic experiments for evidence of this network characteristic in human behavior. The results of the various analyses support the hypothesis that the structure of words in the mental lexicon influences lexical processing. The implications of network science for current models of spoken word recognition, language processing, and cognitive psychology more generally are discussed.

The influence of clustering coefficient on word-learning: how groups of similar sounding words facilitate acquisition

Clustering coefficient, C, measures the extent to which neighbors of a word are also neighbors of each other, and has been shown to influence speech production, speech perception, and several memory-related processes. In this study we examined how C influences word-learning. Participants were trained over three sessions at 1-week intervals, and tested with a picture-naming task on nonword-nonobject pairs. We found an advantage for novel words with high C (the neighbors of this novel word are likely to be neighbors with each other), but only after the 1-week retention period with no additional exposures to the stimuli. The results are consistent with the spreading-activation network-model of the lexicon proposed by Chan and Vitevitch (2009). The influence of C on various language-related processes suggests that characteristics of the individual word are not the only things that influence processing; rather, lexical processing may also be influenced by the relationships that exist among words in the lexicon.

Speaker Sex Influences Processing of Grammatical Gender

Spoken words carry linguistic and indexical information to listeners. Abstractionist models of spoken word recognition suggest that indexical information is stripped away in a process called normalization to allow processing of the linguistic message to proceed. In contrast, exemplar models of the lexicon suggest that indexical information is retained in memory, and influences the process of spoken word recognition. In the present study native Spanish listeners heard Spanish words that varied in grammatical gender (masculine, ending in -o, or feminine, ending in -a) produced by either a male or a female speaker. When asked to indicate the grammatical gender of the words, listeners were faster and more accurate when the sex of the speaker “matched” the grammatical gender than when the sex of the speaker and the grammatical gender “mismatched.” No such interference was observed when listeners heard the same stimuli, but identified whether the speaker was male or female. This finding suggests that indexical information, in this case the sex of the speaker, influences not just processes associated with word recognition, but also higher-level processes associated with grammatical processing. This result also raises questions regarding the widespread assumption about the cognitive independence and automatic nature of grammatical processes.

Path-Length and the Misperception of Speech: Insights from Network Science and Psycholinguistics

Using the analytical methods of network science we examined what could be retrieved from the lexicon when a spoken word is misperceived. To simulate misperceptions in the laboratory, we used a variant of the semantic associates task—the phonological associate task—in which participants heard an English word and responded with the first word that came to mind that sounded like the word they heard, to examine what people actually do retrieve from the lexicon when a spoken word is misperceived. Most responses were 1 link away from the stimulus word in the lexical network. Distant neighbors (words >1 link) were provided more often as responses when the stimulus word had low rather than high degree. Finally, even very distant neighbors tended to be connected to the stimulus word by a path in the lexical network. These findings have implications for the processing of spoken words, and highlight the valuable insights that can be obtained by combining the analytic tools of network science with the experimental tasks of psycholinguistics.

The influence of known-word-frequency on the acquisition of new neighbors in adults: Evidence for exemplar representations in word-learning

Previous studies showed that a new word that is similar to many known words will be learned better than a new word that is similar to few known words. In the present study we created novel words that were phonological neighbours to lexical hermits – or known words that do not have any phonological neighbours – that varied in frequency of occurrence. After several exposures, participants learned a higher proportion of novel words that were neighbours of high-frequency known words than nonwords that were neighbours of low-frequency known words. The present results have implications for abstractionist versus exemplar models of the mental lexicon and language processing, as well as for accounts of word frequency in models of language processing.

The Influence of Closeness Centrality on Lexical Processing

The present study examined how the network science measure known as closeness centrality (which measures the average distance between a node and all other nodes in the network) influences lexical processing. In the mental lexicon, a word such as CAN has high closeness centrality, because it is close to many other words in the lexicon. Whereas, a word such as CURE has low closeness centrality because it is far from other words in the lexicon. In an auditory lexical decision task (Experiment 1) participants responded more quickly to words with high closeness centrality. In Experiment 2 an auditory lexical decision task was again used, but with a wider range of stimulus characteristics. Although, there was no main effect of closeness centrality in Experiment 2, an interaction between closeness centrality and frequency of occurrence was observed on reaction times. The results are explained in terms of partial activation gradually strengthening over time word-forms that are centrally located in the phonological network.

Using complex networks to understand the mental lexicon

Abstract Network science is an emerging discipline drawing from sociology, computer science, physics and a number of other fields to examine complex systems in economical, biological, social, and technological domains. To examine these complex systems, nodes are used to represent individual entities, and links are used to represent relationships between entities, forming a web-like structure, or network, of the entire system. The structure that emerges in these complex networks influences the dynamics of that system. We provide a short review of how this mathematical approach has been used to examine the structure found in the phonological lexicon, and of how subsequent psycholinguistic investigations demonstrate that several of the structural characteristics of the phonological network influence various language-related processes, including word retrieval during the recognition and production of spoken words, recovery from instances of failed lexical retrieval, and the acquisition of word-forms. This approach allows researchers to examine the lexicon at the micro-, meso-, and macro-levels, holding much promise for increasing our understanding of language-related processes and representations.

Speech error and tip of the tongue diary for mobile devices.

The aim of the present study was to address how 43 normal-hearing (NH) and hearing-impaired (HI) listeners subjectively experienced the disturbance generated by four masker conditions (i.e., stationary noise, fluctuating noise, Swedish two-talker babble and English two-talker babble) while listening to speech in two target languages, i.e., Swedish (native) or English (non-native). The participants were asked to evaluate their noise-disturbance experience on a continuous scale from 0 to 10 immediately after having performed each listening condition. The data demonstrated a three-way interaction effect between target language, masker condition, and group (HI versus NH). The HI listeners experienced the Swedish-babble masker as significantly more disturbing for the native target language (Swedish) than for the non-native language (English). Additionally, this masker was significantly more disturbing than each of the other masker types during the perception of Swedish target speech. The NH listeners, on the other hand, indicated that the Swedish speech-masker was more disturbing than the stationary and the fluctuating noise-maskers for the perception of English target speech. The NH listeners perceived more disturbance from the speech maskers than the noise maskers. The HI listeners did not perceive the speech maskers as generally more disturbing than the noise maskers. However, they had particular difficulty with the perception of native speech masked by native babble, a common condition in daily-life listening conditions. These results suggest that the characteristics of the different maskers applied in the current study seem to affect the perceived disturbance differently in HI and NH listeners. There was no general difference in the perceived disturbance across conditions between the HI listeners and the NH listeners.Collections of various types of speech errors have increased our understanding of the acquisition, production, and perception of language. Although such collections of naturally occurring language errors are invaluable for a number of reasons, the process of collecting various types of speech errors presents many challenges to the researcher interested in building such a collection, among them a significant investment of time and effort to obtain a sufficient number of examples to enable statistical analysis. Here we describe a freely accessible website http://spedi.ku.edu that helps users document slips of the tongue, slips of the ear, and tip of the tongue states that they experience firsthand or observe in others. The documented errors are amassed, and made available for other users to analyze, thereby distributing the time and effort involved in collecting errors across a large number of individuals instead of saddling the lone researcher, and facilitating distribution of the collection to other researchers. This approach also addresses some issues related to data curation that hampered previous error collections, and enables the collection to continue to grow over a longer period of time than previous collections. Finally, this web-based tool creates an opportunity for language scientists to engage in outreach efforts to increase the understanding of language disorders and research in the general public.

Phonological neighborhood clustering coefficient influences word learning

Network science is one approach used to analyze complex systems, and has been applied to a complex cognitive system, namely the phonological lexicon (Vitevitch, 2008). One of the measures provided by network science, termed the clustering coefficient or C, influences lexical processes such as speech production (Chan & Vitevitch, 2010) and speech perception (Chan & Vitevitch, 2009). The current study presents evidence of C influencing the process of learning new words. Participants were trained and tested on nonword-nonobject pairs over three lab sessions at one week intervals. Testing occurred immediately after training and after a one week interval. Participants were tested on a picture naming task, a two-alternative-forced-choice task, and a lexical decision task. Results show an advantage for learning new words with a high clustering coefficient. A spreading activation account is used to explain the findings.

The structure of the lexical network influences lexical processing

Network science is an emerging field that uses computational tools from physics, mathematics, computer science, and other fields to examine the structure of complex systems, and explore how that structure might influence processing. In this approach, words in the mental lexicon can be represented as nodes in a network with links connecting words that are phonologically related to each other. Analyses using the mathematical tools of network science suggest that phonological networks from a variety of languages exhibit the characteristics of small-world networks, and share several other structural features. Studies of small-world networks in other domains have demonstrated that such networks are robust to damage, and can be searched very efficiently. Using conventional psycholinguistic tasks, we examined how certain structural characteristics influence the process of spoken word recognition. The findings from these experiments suggest that the lexicon is structured in a non-arbitrary manner, and that this s...