An analysis of the relationships between speech and reading abilities of four hundred and twenty-five first grade children.

Thesis (Ed.M.)--Boston Universit

A longitudinal study of audiovisual speech perception by hearing-impaired children with cochlear implants

The present study investigated the development of audiovisual speech perception skills in children who are prelingually deaf and received cochlear implants. We analyzed results from the Pediatric Speech Intelligibility (Jerger, Lewis, Hawkins, & Jerger, 1980) test of audiovisual spoken word and sentence recognition skills obtained from a large group of young children with cochlear implants enrolled in a longitudinal study, from pre-implantation to 3 years post-implantation. The results revealed better performance under the audiovisual presentation condition compared with auditory-alone and visual-alone conditions. Performance in all three conditions improved over time following implantation. The results also revealed differential effects of early sensory and linguistic experience. Children from oral communication (OC) education backgrounds performed better overall than children from total communication (TC backgrounds. Finally, children in the early-implanted group performed better than children in the late-implanted group in the auditory-alone presentation condition after 2 years of cochlear implant use, whereas children in the late-implanted group performed better than children in the early-implanted group in the visual-alone condition. The results of the present study suggest that measures of audiovisual speech perception may provide new methods to assess hearing, speech, and language development in young children with cochlear implants

Comparing the E-Z Reader Model to Other Models of Eye Movement Control in Reading

The E-Z Reader model provides a theoretical framework for understanding how word identification, visual processing, attention, and oculomotor control jointly determine when and where the eyes move during reading. Thus, in contrast to other reading models reviewed in this article, E-Z Reader can simultaneously account for many of the known effects of linguistic, visual, and oculomotor factors on eye movement control during reading. Furthermore, the core principles of the model have been generalized to other task domains (e.g., equation solving, visual search), and are broadly consistent with what is known about the architecture of the neural systems that support reading

Where is the length effect? A cross-linguistic study.

Many models of speech production assume that one cannot begin to articulate a word before all its segmental units are inserted into the articulatory plan. Moreover, some of these models assume that segments are serially inserted from left to right. As a consequence, latencies to name words should increase with word length. In a series of five experiments, however, we showed that the time to name a picture or retrieve a word associated with a symbol is not affected by the length of the word. Experiments 1 and 2 used French materials and participants, while Experiments 3, 4 and 5 were conducted with English materials and participants. These results are discussed in relation to current models of speech production, and previous reports of length effects are reevaluated in light of these findings. We conclude that if words are encoded serially, then articulation can start before an entire phonological word has been encoded

Durations of repeated non-words for children with cochlear implants

Durations of syllables for repeated non-words were calculated for 76 children with cochlear implants (CIs) and 16 children with normal hearing (NH). Average syllable durations did not differ significantly between the groups, however a final syllable lengthening ratio in CI children was significantly shorter than for their NH peers. Measures of hearing related demographics were not correlated with CI syllable measures

#Bieber + #Blast = #BieberBlast: Early Prediction of Popular Hashtag Compounds

Compounding of natural language units is a very common phenomena. In this paper, we show, for the first time, that Twitter hashtags which, could be considered as correlates of such linguistic units, undergo compounding. We identify reasons for this compounding and propose a prediction model that can identify with 77.07% accuracy if a pair of hashtags compounding in the near future (i.e., 2 months after compounding) shall become popular. At longer times T = 6, 10 months the accuracies are 77.52% and 79.13% respectively. This technique has strong implications to trending hashtag recommendation since newly formed hashtag compounds can be recommended early, even before the compounding has taken place. Further, humans can predict compounds with an overall accuracy of only 48.7% (treated as baseline). Notably, while humans can discriminate the relatively easier cases, the automatic framework is successful in classifying the relatively harder cases.Comment: 14 pages, 4 figures, 9 tables, published in CSCW (Computer-Supported Cooperative Work and Social Computing) 2016. in Proceedings of 19th ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2016

Reading the Readers: Modelling Complex Humanities Processes to Build Cognitive Systems

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes the initial stages in the development of a computer system designed to aid historians in the reading of the stylus tablets. A detailed investigation was undertaken, using Knowledge Elicitation techniques borrowed from Artificial IntelliJOURce, Cognitive Psychology, and Computational Linguistics, to elicit the processes experts use whilst reading an ancient text. The resulting model was used as the basis of a computer architecture to construct a system which takes in images of the tablets and outputs plausible interpretations of the documents. It is demonstrated that using Knowledge Elicitation techniques can further the understanding of complex processes in the humanities, and that these techniques can provide an underlying structure for the basis of a computer system that replicates that process. As such it provides significant insight into how experts work in the humanities, whilst providing the means to develop tools to assist them in their complex task

Efficient Estimation of Word Representations in Vector Space

We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Furthermore, we show that these vectors provide state-of-the-art performance on our test set for measuring syntactic and semantic word similarities