scholarly journals How vocabulary size in two languages relates to efficiency in spoken word recognition by young Spanish–English bilinguals

2009 ◽  
Vol 37 (4) ◽  
pp. 817-840 ◽  
Author(s):  
VIRGINIA A. MARCHMAN ◽  
ANNE FERNALD ◽  
NEREYDA HURTADO
Keyword(s):  
Word Recognition ◽  
Speech Processing ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Vocabulary Knowledge ◽  
Vocabulary Size ◽  
Processing Efficiency ◽  
Lexical Development ◽  
Online Processing ◽  
Speed And Accuracy

ABSTRACTResearch using online comprehension measures with monolingual children shows that speed and accuracy of spoken word recognition are correlated with lexical development. Here we examined speech processing efficiency in relation to vocabulary development in bilingual children learning both Spanish and English (n=26 ; 2 ; 6). Between-language associations were weak: vocabulary size in Spanish was uncorrelated with vocabulary in English, and children's facility in online comprehension in Spanish was unrelated to their facility in English. Instead, efficiency of online processing in one language was significantly related to vocabulary size in that language, after controlling for processing speed and vocabulary size in the other language. These links between efficiency of lexical access and vocabulary knowledge in bilinguals parallel those previously reported for Spanish and English monolinguals, suggesting that children's ability to abstract information from the input in building a working lexicon relates fundamentally to mechanisms underlying the construction of language.

scholarly journals Spoken word recognition by Latino children learning Spanish as their first language

2007 ◽  
Vol 34 (2) ◽  
pp. 227-249 ◽  
Author(s):  
NEREYDA HURTADO ◽  
VIRGINIA A. MARCHMAN ◽  
ANNE FERNALD
Keyword(s):  
Word Recognition ◽  
Language Learning ◽  
Speech Processing ◽  
English Learners ◽  
Spoken Word Recognition ◽  
Spoken Language ◽  
Spoken Word ◽  
Older Children ◽  
Vocabulary Size ◽  
The Impact

Research on the development of efficiency in spoken language understanding has focused largely on middle-class children learning English. Here we extend this research to Spanish-learning children (n=49; M=2;0; range=1;3–3;1) living in the USA in Latino families from primarily low socioeconomic backgrounds. Children looked at pictures of familiar objects while listening to speech naming one of the objects. Analyses of eye movements revealed developmental increases in the efficiency of speech processing. Older children and children with larger vocabularies were more efficient at processing spoken language as it unfolds in real time, as previously documented with English learners. Children whose mothers had less education tended to be slower and less accurate than children of comparable age and vocabulary size whose mothers had more schooling, consistent with previous findings of slower rates of language learning in children from disadvantaged backgrounds. These results add to the cross-linguistic literature on the development of spoken word recognition and to the study of the impact of socioeconomic status (SES) factors on early language development.

Hesitations and clarifications on a model to abandon feedback

2000 ◽  
Vol 23 (3) ◽  
pp. 347-347
Author(s):  
Louisa M. Slowiaczek
Keyword(s):  
Word Recognition ◽  
Speech Processing ◽  
Spoken Word Recognition ◽  
Spoken Word

Hesitations about accepting whole-heartedly Norris et al.'s suggestion to abandon feedback in speech processing models concern (1) whether accounting for all available data justifies additional layers of complexity in the model and (2) whether characterizing Merge as non- interactive is valid. Spoken word recognition studies support the nature of Merge's lexical level and suggest that phonemes should comprise the prelexical level.

scholarly journals Clustering coefficients of lexical neighborhoods

2010 ◽  
Vol 5 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Nicholas Altieri ◽  
Thomas Gruenenfelder ◽  
David B. Pisoni
Keyword(s):  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Neighborhood Density ◽  
Clustering Coefficient ◽  
Response Latencies ◽  
Graph Theoretic ◽  
Word Repetition ◽  
Lexical Neighborhoods ◽  
Speed And Accuracy

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.

scholarly journals Contra assertions, feedback improves word recognition

2021 ◽  
Author(s):  
James Magnuson ◽  
Samantha Grubb ◽  
Anne Marie Crinnion ◽  
Sahil Luthra ◽  
Phoebe Gaston
Keyword(s):  
Word Recognition ◽  
Speech Processing ◽  
Recognition Performance ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Feedback Signal ◽  
Activation Model ◽  
Trace Model ◽  
Interactive Activation ◽  
Joint Probabilities

Norris and Cutler (in press) revisit their arguments that (lexical-to-sublexical) feedback cannot improve word recognition performance, based on the assumption that feedback must boost signal and noise equally. They also argue that demonstrations that feedback improves performance (Magnuson, Mirman, Luthra, Strauss, & Harris, 2018) in the TRACE model of spoken word recognition (McClelland & Elman, 1986) were artifacts of converting activations to response probabilities. We first evaluate their claim that feedback in an interactive activation model must boost noise and signal equally. This is not true in a fully interactive activation model such as TRACE, where the feedback signal does not simply mirror the feedforward signal; it is instead shaped by joint probabilities over lexical patterns, and the dynamics of lateral inhibition. Thus, even under high levels of noise, lexical feedback will selectively boost signal more than noise. We demonstrate that feedback promotes faster word recognition and preserves accuracy under noise whether one uses raw activations or response probabilities. We then document that lexical feedback selectively boosts signal (i.e., lexically-coherent series of phonemes) more than noise by tracking sublexical (phoneme) activations under noise with and without feedback. Thus, feedback in a model like TRACE does improve word recognition, exactly by selective reinforcement of lexically-coherent signal. We conclude that whether lexical feedback is integral to human speech processing is an empirical question, and briefly review a growing body of work at behavioral and neural levels that is consistent with feedback and inconsistent with autonomous (non-feedback) architectures.

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