Phonological but not semantic influences on the speech-to-song illusion

Using Complex Networks in the Hearing Sciences

In this Point of View, we review a number of recent discoveries from the emerging, interdisciplinary field of Network Science , which uses graph theoretic techniques to understand complex systems. In the network science approach, nodes represent entities in a system, and connections are placed between nodes that are related to each other to form a web-like network . We discuss several studies that demonstrate how the micro-, meso-, and macro-level structure of a network of phonological word-forms influence spoken word recognition in listeners with normal hearing and in listeners with hearing loss. Given the discoveries made possible by this new approach and the influence of several complex network measures on spoken word recognition performance we argue that speech recognition measures-originally developed in the late 1940s and routinely used in clinical audiometry-should be revised to reflect our current understanding of spoken word recognition. We also discuss other ways in which the tools of network science can be used in Speech and Hearing Sciences and Audiology more broadly.

Identifying the phonological backbone in the mental lexicon

Previous studies used techniques from network science to identify individual nodes and a set of nodes that were "important" in a network of phonological word-forms from English. In the present study we used a network simplification process-known as the backbone-that removed redundant edges to extract a subnetwork of "important" words from the network of phonological word-forms. The backbone procedure removed 68.5% of the edges in the original network to extract a backbone with a giant component containing 6,211 words. We compared psycholinguistic and network measures of the words in the backbone to the words that did not survive the backbone extraction procedure. Words in the backbone occurred more frequently in the language, were shorter in length, were similar to more phonological neighbors, and were closer to other words than words that did not survive the backbone extraction procedure. Words in the backbone of the phonological network might form a "kernel lexicon"-a small but essential set of words that allows one to communicate in a wide-range of situations-and may provide guidance to clinicians and researchers on which words to focus on to facilitate typical development, or to accelerate rehabilitation efforts. The backbone extraction method may also prove useful in other applications of network science to the speech, language, hearing and cognitive sciences.

The Resilience of the Phonological Network May Have Implications for Developmental and Acquired Disorders

A central tenet of network science states that the structure of the network influences processing. In this study of a phonological network of English words we asked: how does damage alter the network structure (Study 1)? How does the damaged structure influence lexical processing (Study 2)? How does the structure of the intact network "protect" processing with a less efficient algorithm (Study 3)? In Study 1, connections in the network were randomly removed to increasingly damage the network. Various measures showed the network remained well-connected (i.e., it is resilient to damage) until ~90% of the connections were removed. In Study 2, computer simulations examined the retrieval of a set of words. The performance of the model was positively correlated with naming accuracy by people with aphasia (PWA) on the Philadelphia Naming Test (PNT) across four types of aphasia. In Study 3, we demonstrated another way to model developmental or acquired disorders by manipulating how efficiently activation spread through the network. We found that the structure of the network "protects" word retrieval despite decreases in processing efficiency; words that are relatively easy to retrieve with efficient transmission of priming remain relatively easy to retrieve with less efficient transmission of priming. Cognitive network science and computer simulations may provide insight to a wide range of speech, language, hearing, and cognitive disorders.

The influence of memory on the speech-to-song illusion

In the speech-to-song illusion a spoken phrase is presented repeatedly and begins to sound as if it is being sung. Anecdotal reports suggest that subsequent presentations of a previously heard phrase enhance the illusion, even if several hours or days have elapsed between presentations. In Experiment 1, we examined in a controlled laboratory setting whether memory traces for a previously heard phrase would influence song-like ratings to a subsequent presentation of that phrase. The results showed that word lists that were played several times throughout the experimental session were rated as being more song-like at the end of the experiment than word lists that were played only once in the experimental session. In Experiment 2, we examined if the memory traces that influenced the speech-to-song illusion were abstract in nature or exemplar-based by playing some word lists several times during the experiment in the same voice and playing other word lists several times during the experiment but in different voices. The results showed that word lists played in the same voice were rated as more song-like at the end of the experiment than word lists played in different voices. Many previous studies have examined how various aspects of the stimulus itself influences the perception of the speech-to-song illusion. The results of the present experiments demonstrate that memory traces of the stimulus also influence the speech-to-song illusion.

What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach

Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retrieve a sufficient number of words to assess if it could replicate the behavioral findings. The cognitive network model successfully replicated the behavioral findings in Simulations 1 and 2. However, in Simulation 3a, the cognitive network did not replicate the behavioral findings, perhaps because an additional mechanism was not implemented in the model. However, in Simulation 3b, when the decay parameter in spreadr was manipulated to model this mechanism the cognitive network model successfully replicated the behavioral findings. The results suggest that models of cognition need to take into account the multi-scale structure that exists among representations in memory, and how that structure can influence processing.

Does age affect perception of the Speech-to-Song Illusion?

The Speech-to-Song Illusion is an auditory illusion that occurs when a spoken phrase is repeatedly presented. After several presentations, listeners report that the phrase seems to be sung rather than spoken. Previous work [1] indicates that the mechanisms-priming, activation, and satiation-found in the language processing model, Node Structure Theory (NST), may account for the Speech-to-Song Illusion. NST also accounts for other language-related phenomena, including increased experiences in older adults of the tip-of-the-tongue state (where you know a word, but can't retrieve it). Based on the mechanism in NST used to account for the age-related increase in the tip-of-the-tongue phenomenon, we predicted that older adults may be less likely to experience the Speech-to-Song Illusion than younger adults. Adults of a wide range of ages heard a stimulus known to evoke the Speech-to-Song Illusion. Then, they were asked to indicate if they experienced the illusion or not (Study 1), to respond using a 5-point song-likeness rating scale (Study 2), or to indicate when the percept changed from speech to song (Study 3). The results of these studies suggest that the illusion is experienced with similar frequency and strength, and after the same number of repetitions by adult listeners regardless of age.