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1. Feedback in the Time-Invariant String Kernel model of spoken word recognition

   Magnuson, J.; You, H. (July 2018, Proceedings of the Cognitive Science Society)

   The Time-Invariant String Kernel (TISK) model of spoken word recognition (Hanngan et al., 2013) is an interactive activation model like TRACE (McClelland & Elman, 1986). However, it uses orders of magnitude fewer nodes and connections because it replaces TRACE's time-specific duplicates of phoneme and word nodes with time-invariant nodes based on a string kernel representation (essentially a phoneme-by-phoneme matrix, where a word is encoded as by all ordered open diphones it contains; e.g., cat has /kæ/, /æt/, and /kt/). Hannagan et al. (2013) showed that TISK behaves similarly to TRACE in the time course of phonological competition and even word-specific recognition times. However, the original implementation did not include feedback from words to diphone nodes, precluding simulation of top-down effects. Here, we demonstrate that TISK can be easily adapted to lexical feedback, affording simulation of top-down effects as well as allowing the model to demonstrate graceful degradation given noisy inputs. 

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2. Universal Features in Phonological Neighbor Networks

   https://doi.org/10.3390/e20070526  

   Brown, Kevin; Allopenna, Paul; Hunt, William; Steiner, Rachael; Saltzman, Elliot; McRae, Ken; Magnuson, James (July 2018, Entropy)

   Human speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that phonological neighbors (two forms [words] that differ by one phoneme) compete significantly for recognition as a spoken word is heard. This definition of phonological similarity can be extended to an entire corpus of forms to produce a phonological neighbor network (PNN). We study PNNs for five languages: English, Spanish, French, Dutch, and German. Consistent with previous work, we find that the PNNs share a consistent set of topological features. Using an approach that generates random lexicons with increasing levels of phonological realism, we show that even random forms with minimal relationship to any real language, combined with only the empirical distribution of language-specific phonological form lengths, are sufficient to produce the topological properties observed in the real language PNNs. The resulting pseudo-PNNs are insensitive to the level of lingustic realism in the random lexicons but quite sensitive to the shape of the form length distribution. We therefore conclude that “universal” features seen across multiple languages are really string universals, not language universals, and arise primarily due to limitations in the kinds of networks generated by the one-step neighbor definition. Taken together, our results indicate that caution is warranted when linking the dynamics of human spoken word recognition to the topological properties of PNNs, and that the investigation of alternative similarity metrics for phonological forms should be a priority. 

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3. Auditory Word Comprehension Is Less Incremental in Isolated Words

   https://doi.org/10.1162/nol_a_00084  

   Gaston, Phoebe; Brodbeck, Christian; Phillips, Colin; Lau, Ellen (January 2023, Neurobiology of Language)

   Abstract Partial speech input is often understood to trigger rapid and automatic activation of successively higher-level representations of words, from sound to meaning. Here we show evidence from magnetoencephalography that this type of incremental processing is limited when words are heard in isolation as compared to continuous speech. This suggests a less unified and automatic word recognition process than is often assumed. We present evidence from isolated words that neural effects of phoneme probability, quantified by phoneme surprisal, are significantly stronger than (statistically null) effects of phoneme-by-phoneme lexical uncertainty, quantified by cohort entropy. In contrast, we find robust effects of both cohort entropy and phoneme surprisal during perception of connected speech, with a significant interaction between the contexts. This dissociation rules out models of word recognition in which phoneme surprisal and cohort entropy are common indicators of a uniform process, even though these closely related information-theoretic measures both arise from the probability distribution of wordforms consistent with the input. We propose that phoneme surprisal effects reflect automatic access of a lower level of representation of the auditory input (e.g., wordforms) while the occurrence of cohort entropy effects is task sensitive, driven by a competition process or a higher-level representation that is engaged late (or not at all) during the processing of single words. 

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4. Observing gestures during L2 word learning facilitates differentiation between unfamiliar speech sounds and word meanings

   Morett, Laura M (August 2023, Proceedings of the Cognitive Science Society)

   Goldwater, M; Angora, F; Hayes, B; Ong, D (Ed.)

   This study investigated how observing pitch gestures conveying lexical tones and representational gestures conveying word meanings when learning L2 Mandarin words differing in lexical tone affects their subsequent semantic and phonological processing in L1 English speakers using the N400 event-related potential (ERP). Larger N400s for English target words mismatching vs. matching Mandarin prime words in meaning were observed for words learned with pitch and representational gesture, but not no gesture. Additionally, larger N400s for Mandarin target words mismatching vs. matching Mandarin prime words in lexical tone were observed for words learned with pitch gesture, but not representational or no gesture. These findings provide the first ERP evidence that observing gestures conveying phonological and semantic information during L2 word learning enhances subsequent phonological and semantic processing of learned L2 words. 

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5. Very Young Infants’ Sensitivity to Consonant Mispronunciations in Word Recognition

   Beech, Caroline; Swingley, Daniel (June 2023, University of California)

   Goldwater, M; Anggoro, FK; Hayes, BK; Ong, DC (Ed.)

   Before they start to talk, infants learn the form and meaning of many common words. In the present work, we investigated the nature of this word knowledge, testing the specificity of very young infants’ (6-14 months) phonological represen- tations in an internet-based language-guided-looking task using correct pronunciations and initial-consonant mispronunciations of common words. Across the current sample (n=78 out of 96 pre-registered), infants’ proportion looking to the target (named image) versus the distracter was significantly lower when the target word was mispronounced, indicating sensitivity to phonological deviation. Performance patterns varied by age group. The youngest group (6-8 months, n=30) was at chance in both conditions, the middle group (9-11 months, n=21) showed significant recognition of correct pronunciations and a marginal mispronunciation effect, and the oldest age group (12-14 months, n=27) demonstrated the mature pattern: significant recognition and a significant mispronunciation effect. Ongoing work is completing the pre-registered sample size. 

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