The development of reading depends on phonological awareness across all languages so far studied. Languages vary in the consistency with which phonology is represented in orthography. This results in developmental differences in the grain size of lexical representations and accompanying differences in developmental reading strategies and the manifestation of dyslexia across orthographies. Differences in lexical representations and reading across languages leave developmental “footprints” in the adult lexicon. The lexical organization and processing strategies that are characteristic of skilled reading in different orthographies are affected by different developmental constraints in different writing systems. The authors develop a novel theoretical framework to explain these cross-language data, which they label a psycholinguistic grain size theory of reading and its development.

Reading acquisition, developmental dyslexia, and skilled reading across languages: a psycholinguistic grain size theory.

Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data This textbook provides a straightforward introduction to the statistical analysis of language Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data

Analyzing linguistic data : a practical introduction to statistics using R

Word frequency is the most important variable in research on word processing and memory. Yet, the main criterion for selecting word frequency norms has been the availability of the measure, rather than its quality. As a result, much research is still based on the old Kucera and Francis frequency norms. By using the lexical decision times of recently published megastudies, we show how bad this measure is and what must be done to improve it. In particular, we investigated the size of the corpus, the language register on which the corpus is based, and the definition of the frequency measure. We observed that corpus size is of practical importance for small sizes (depending on the frequency of the word), but not for sizes above 16–30 million words. As for the language register, we found that frequencies based on television and film subtitles are better than frequencies based on written sources, certainly for the monosyllabic and bisyllabic words used in psycholinguistic research. Finally, we found that lemma frequencies are not superior to word form frequencies in English and that a measure of contextual diversity is better than a measure based on raw frequency of occurrence. Part of the superiority of the latter is due to the words that are frequently used as names. Assembling a new frequency norm on the basis of these considerations turned out to predict word processing times much better than did the existing norms (including Kucera & Francis and Celex). The new SUBTL frequency norms from the SUBTLEXUS corpus are freely available for research purposes from http://brm.psychonomic-journals.org/content/supplemental, as well as from the University of Ghent and Lexique Web sites.

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Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English

Advances in computational linguistics and discourse processing have made it possible to automate many language- and text-processing mechanisms. We have developed a computer tool called Coh-Metrix, which analyzes texts on over 200 measures of cohesion, language, and readability. Its modules use lexicons, part-of-speech classifiers, syntactic parsers, templates, corpora, latent semantic analysis, and other components that are widely used in computational linguistics. After the user enters an English text, Coh-Metrix returns measures requested by the user. In addition, a facility allows the user to store the results of these analyses in data files (such as Text, Excel, and SPSS). Standard text readability formulas scale texts on difficulty by relying on word length and sentence length, whereas Coh-Metrix is sensitive to cohesion relations, world knowledge, and language and discourse characteristics.

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Coh-Metrix: Analysis of text on cohesion and language

Event-related brain potentials (ERPs) can reveal online processing differences between native speakers and second language (L2) learners during language comprehension. Using the P600 as a measure of native-likeness, we investigated processing of grammatical gender agreement in highly proficient immersed Romance L2 learners of Dutch. We demonstrate that these late learners consistently fail to show native-like sensitivity to gender violations. This appears to be due to a combination of differences from the gender marking in their L1 and the relatively opaque Dutch gender system. We find that L2 use predicts the effect magnitude of non-finite verb violations, a relatively regular and transparent construction, but not that of gender agreement violations. There were no effects of age of acquisition, length of residence, proficiency or offline gender knowledge. Additionally, a within-subject comparison of stimulus modalities (written vs. auditory) shows that immersed learners may show some of the effects only in the auditory modality; in non-finite verb violations, an early native-like N400 was only present for auditory stimuli. However, modality failed to influence the response to gender. Taken together, the results confirm the persistent problems of Romance learners of Dutch with online gender processing and show that they cannot be overcome by reducing task demands related to the modality of stimulus presentation.

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R. H. Baayen

Papers

The CELEX Lexical Database (CD-ROM)