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•Anodal HD-tDCS facilitated verb learning.•Enhanced connectivity between IFG and TPJ improved verb learning.•Robust word learning linked to enhanced network interactions.•Behavioral activation of one area and tDCS of another area can induce network modulation. Neurobehavioral studies have provided evidence for the effectiveness of anodal tDCS on language production, by stimulation of the left Inferior Frontal Gyrus (IFG) or of left Temporo-Parietal Junction (TPJ). However, tDCS is currently not used in clinical practice outside of trials, because behavioral effects have been inconsistent and underlying neural effects unclear. Here, we propose to elucidate the neural correlates of verb and noun learning and to determine if they can be modulated with anodal high-definition (HD) tDCS stimulation. Thirty-six neurotypical participants were randomly allocated to anodal HD-tDCS over either the left IFG, the left TPJ, or sham stimulation. On day one, participants performed a naming task (pre-test). On day two, participants underwent a new-word learning task with rare nouns and verbs concurrently to HD-tDCS for 20 min. The third day consisted of a post-test of naming performance. EEG was recorded at rest and during naming on each day. Verb learning was significantly facilitated by left IFG stimulation. HD-tDCS over the left IFG enhanced functional connectivity between the left IFG and TPJ and this correlated with improved learning. HD-tDCS over the left TPJ enabled stronger local activation of the stimulated area (as indexed by greater alpha and beta-band power decrease) during naming, but this did not translate into better learning. Thus, tDCS can induce local activation or modulation of network interactions. Only the enhancement of network interactions, but not the increase in local activation, leads to robust improvement of word learning. This emphasizes the need to develop new neuromodulation methods influencing network interactions. Our study suggests that this may be achieved through behavioral activation of one area and concomitant activation of another area with HD-tDCS.

The role of verbal labels in the assimilation of information on novel objects depending on the speech learning strategy was studied by assessing the effectiveness of the recognition of novel objects learned using fast mapping and explicit coding strategies, taking oculomotor activity into account. A total of 32 subjects were presented with visual images of eight new plant fruits, each one eight times, with auditory presentation of a unique labels in 50% of cases and a general verbal labels in the other 50%. Visual search of a target image among distractors was used as test task. The findings indicated that the fast mapping provided faster acquisition of new words than explicit encoding. The unique verbal labels of new fruits was found to have a positive influence on performance of the visual search task, this type of designation having greater significance being characteristic of fast mapping in contrast to explicit encoding.

Purpose: Three studies investigated novel word learning, some requiring phonological production, each involving between 11 and 17 individuals with Down syndrome, and between 15 and 24 typically developing individuals matched for receptive vocabulary. The effect of stimuli wordlikeness and incidental procedure-based memory demands were examined to see whether these may account for an apparent impairment in word learning in Down syndrome demonstrated in earlier research. Method: Paired associate word and nonword learning tasks were presented, requiring participants to learn the names of novel characters. The nonword stimuli varied in the degree of wordlikeness in 2 studies. A third study investigated extraneous task demand. Results: Across 3 studies, there was no suggestion of a word learning deficit associated with Down syndrome (2p for the main effect of group of 0.03, 0.11, and 0.03, respectively), despite the level of phonological representation required. There was evidence that novel word learning by participants with Down syndrome exceeded that which their verbal short-term memory capacity would predict. Conclusions: Vocabulary acquisition in Down syndrome may not rely on verbal short-term memory to the same extent as in typically developing children, lending support to the suggestion that new word learning may be underpinned by an additional memory process.

The aim was to test the use of eye-tracking methodology for the early detection of ASD in a task of association between unfamiliar objects and pseudowords. Significant differences were found between ASD (n = 57) and TD (n = 57) Spanish speaking toddlers in the number and time of fixation. The TD children showed more and longer fixations on eyes and mouth while the ASD children attended almost exclusively to objects, making it difficult to integrate lexical and phonological information. Moreover, the TD toddlers looked at the mouth when the pseudoword was produced while the ASD toddlers did not. Gaze fixation on eyes and mouth during word learning recorded by eye-tracking may be used as a biomarker for the early diagnosis of ASD.

In a masked form priming lexical decision task, orthographically related word primes cause null or inhibitory priming relative to unrelated controls because of lexical competition between primes and targets, whereas orthographically related nonword primes lead to facilitation because nonwords are not lexically represented and hence do not evoke lexical competition. This prime lexicality effect (PLE) has been used as an index of new word lexicalization in the developing lexicon by using to-be-learned words and their orthographic neighbors as primes and targets, respectively. Experiment 1 confirmed an inhibitory effect of −46 ms among native English speakers and faciliatory effects of 52 ms by Japanese English learners without critical word training. In Experiment 2 , Japanese English learners studied novel English words while performing a meaning-based, form-based, or no task during learning. Recall measures indicated a dissociation between these two types of processing, with a form-based task leading to greater recall of L2 words and a meaning-based task leading to greater recall of L1 words. Results indicated that all three learning conditions produced neither facilitation nor inhibition (null priming effect). Taken together, the results of the two experiments demonstrate that the PLE can occur in a second language (L2) and that the training procedure can yield at least partial lexicalization of new L2 words.

Short message services (SMS), microblogging tools, instant message apps, and commercial websites produce numerous short text messages every day. These short text messages are usually guaranteed to reach mass audience with low cost. Spammers take advantage of short texts by sending bulk malicious or unwanted messages. Short texts are difficult to classify because of their shortness, sparsity, rapidness, and informal writing. The effectiveness of the hidden Markov model (HMM) for short text classification has been illustrated in our previous study. However, the HMM has limited capability to handle new words, which are mostly generated by informal writing. In this paper, a hybrid model is proposed to address the informal writing issue by weighting new words for fast short text filtering with high accuracy. The hybrid model consists of an artificial neural network (ANN) and an HMM, which are used for new word weighting and spam filtering, respectively. The weight of a new word is calculated based on the weights of its neighbor, along with the spam and ham (i.e., not spam) probabilities of short text message predicted by the ANN. Performance evaluations on benchmark datasets, including the SMS message data maintained by University of California, Irvine; the movie reviews, and the customer reviews are conducted. The hybrid model operates at a significantly higher speed than deep learning models. The experiment results show that the proposed hybrid model outperforms other prominent machine learning algorithms, achieving a good balance between filtering throughput and accuracy.

Extracurricular reading is important for learning foreign languages. Text recommendation systems typically classify users and documents into levels, and then match users with documents at the same level. Although this approach can be effective, it has two significant shortcomings. First, the levels assume a standard order of language acquisition and cannot be personalized to the users’ learning patterns. Second, recommendation decisions are not transparent because the leveling algorithms can be difficult for users to interpret. We propose a novel method for text recommendation that addresses these two issues. To enhance personalization, an open, editable learner model estimates user knowledge of each word in the foreign language. The documents are ranked by new-word density (NWD) – that is, the percentage of words that are new to the user in the document. The system then recommends documents according to a user-specified target NWD. This design offers complete transparency as users can scrutinize recommendations by reviewing the NWD estimation of the learner model. This article describes an implementation of this method in a mobile app for learners of Chinese as a foreign language. Evaluation results show that users were able to manipulate the learner model and NWD parameters to adjust the difficulty of the recommended documents. In a survey, users reported satisfaction with both the concept and implementation of this text recommendation method.

PurposeAdvanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.Design/methodology/approachIn this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.FindingsThe complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.Originality/valueThe proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

Background/Objectives. Vocabulary acquisition is a lifelong process, with the most rapid growth occurring from early childhood to school age. Different contextual factors influence how new vocabulary is acquired across various age groups during reading. Methods. We studied the process of new word acquisition in different constraining contexts in adolescents aged 11–17 years old and how individual differences in reading comprehension, vocabulary, and verbal working memory affect word acquisition. In the learning stage, the new words were presented in sentences with low and high contextual constraints, and word acquisition was assessed in a word recognition test where behavioral measures and the N400 and P600 components of the event-related potentials (ERPs) were examined. Results. Our study reveals that while the accuracy of word recognition was at a chance level, adolescents had faster responses to words learned in high-constraining contexts compared to words from low-constraining contexts. Neural responses were influenced by context, with explicit recollection processes reflected in the P600 being modulated by the type of sentence constraint, while implicit familiarity related to the N400 did not show this effect. Higher reading comprehension, vocabulary, and verbal working memory scores improved accuracy, while reaction times were improved by just vocabulary. Additionally, reading comprehension and vocabulary impacted the implicit N400 old/new effect, and reading comprehension correlated with explicit recognition processes (P600 old/new effect). Conclusions. Therefore, the present study showed that the type of constraint of new word learning and individual skills affected the word acquisition process in adolescents.

This study focused on the associative learning of new word forms in the first language and haptic stimuli. In this study, healthy Japanese participants performed three-step tasks. First, participants made nine subjective evaluations of haptic stimuli using five-point semantic differential scales (e.g., regarding stickiness, scored from 1 (not sticky) to 5 (sticky)). Second, the participants carried out learning and recognition tasks for associative pairs of new (meaningless) word forms in their first language (Japanese) and haptic stimulus (H condition), and performed learning and recognition tasks for new (meaningless) word forms only (W condition). The order of conditions was counterbalanced among participants. Third, participants performed free recall tasks. The results of the recognition tasks showed that the proportions and response times of the W condition were better and faster, respectively, than those of the H condition. Furthermore, preference of haptic features negatively correlated with free recall scores of the H condition; however, there was no significant difference between the free recall scores of the H and W conditions. Our results suggest that new word forms were learned better than associative pairs of new word forms and haptic stimuli in a single day of learning. Furthermore, the free recall performance of word forms associated with haptic features could also be affected by their subjective evaluation (preference).