Previous research has shown that vocabulary size affects performance on laboratory word production tasks. Individuals who know many words show faster lexical access and retrieve more words belonging to pre-specified categories than individuals who know fewer words. The present study examined the relationship between receptive vocabulary size and speaking skills as assessed in a natural sentence production task. We asked whether measures derived from spontaneous responses to everyday questions correlate with the size of participants’ vocabulary. Moreover, we assessed the suitability of automatic speech recognition (ASR) for the analysis of participants’ responses in complex language production data. We found that vocabulary size predicted indices of spontaneous speech: individuals with a larger vocabulary produced more words and had a higher speech-silence ratio compared to individuals with a smaller vocabulary. Importantly, these relationships were reliably identified using manual and automated transcription methods. Taken together, our results suggest that spontaneous speech elicitation is a useful method to investigate natural language production and that automatic speech recognition can alleviate the burden of labor-intensive speech transcription.
What mechanisms underlie people’s ability to use cross- situational statistics to learn the meanings of words? Here we present a large-scale evaluation of two major models of cross-situational learning: associative (Kachergis, Yu, & Shiffrin, 2012a) and hypothesis testing (Trueswell, Medina, Hafri, & Gleitman, 2013). We fit each model individually to over 1500 participants across seven experiments with a wide range of conditions. We find that the associative model better captures the full range of individual differences and conditions when learning is cross-situational, although the hypothesis testing approach outperforms it when there is no referential ambiguity during training.
A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual-path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within-language priming is small and difficult to detect statistically.
To test whether error-driven implicit learning can explain cross-language structural priming, we implemented three different models of bilingual sentence production: Spanish-English, verb-final Dutch-English, and verb-medial Dutch-English. With these models, we conducted simulation experiments that all revealed clear and strong cross-language priming effects.One of these experiments included structures with different word order between the two languages. This enabled us to distinguish between the error-driven learning account of structural priming and an alternative hybrid account which predicts that identical word order is required for cross-language priming. Cross-language priming did occur in our model between structures with different word order. This is in line with results from behavioural experiments.The results of the three experiments reveal varying degrees of evidence for stronger within-language priming than cross-language priming. This is consistent with results from behavioural studies.Overall, our findings support the viability of error-driven implicit learning as an account of cross-language structural priming.
In face-to-face discourse, listeners exploit cues in the input to generate predictions about upcoming words. Moreover, in addition to speech, speakers produce a multitude of visual signals, such as iconic gestures, which listeners readily integrate with incoming words. Previous studies have shown that processing of target words is facilitated when these are embedded in predictable compared to non-predictable discourses and when accompanied by iconic compared to meaningless gestures. In the present study, we investigated the interaction of both factors. We recorded electroencephalogram from 60 Dutch adults while they were watching videos of an actress producing short discourses. The stimuli consisted of an introductory and a target sentence; the latter contained a target noun. Depending on the preceding discourse, the target noun was either predictable or not. Each target noun was paired with an iconic gesture and a gesture that did not convey meaning. In both conditions, gesture presentation in the video was timed such that the gesture stroke slightly preceded the onset of the spoken target by 130 ms. Our ERP analyses revealed independent facilitatory effects for predictable discourses and iconic gestures. However, the interactive effect of both factors demonstrated that target processing (i.e., gesture-speech integration) was facilitated most when targets were part of predictable discourses and accompanied by an iconic gesture. Our results thus suggest a strong intertwinement of linguistic predictability and non-verbal gesture processing where listeners exploit predictive discourse cues to pre-activate verbal and non-verbal representations of upcoming target words.
In face-to-face discourse, listeners exploit cues in the input to generate predictions about upcoming words. Moreover, in addition to speech, speakers produce a multitude of visual signals, such as iconic gestures, which listeners readily integrate with incoming words. Previous studies have shown that processing of target words is facilitated when these are embedded in predictable compared to non- predictable discourses and when accompanied by iconic compared to meaningless gestures. In the present study, we investigated the interaction of both factors. We recorded electroencephalogram from 60 Dutch adults while they were watching videos of an actress producing short discourses. The stimuli consisted of an introductory and a target sentence; the latter contained a target noun. Depending on the preceding discourse, the target noun was either predictable or not. Each target noun was paired with an iconic gesture and a gesture that did not convey meaning. In both conditions, gesture presentation in the video was timed such that the gesture stroke slightly preceded the onset of the spoken target by 130 ms. Our ERP analyses revealed independent facilitatory effects for predictable discourses and iconic gestures. However, the interactive effect of both factors demonstrated that target processing (i.e., gesture-speech integration) was facilitated most when targets were part of predictable discourses and accompanied by an iconic gesture. Our results thus suggest a strong intertwinement of linguistic predictability and non-verbal gesture processing where listeners exploit predictive discourse cues to pre-activate verbal and non-verbal representations of upcoming target words.
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