Vocabulary learning is central to reading ability and academic achievement. Vocabulary researchers and educators have viewed its essence as a process of associating the pronunciations and meanings of words in memory, and they have paid little attention to the contribution that spellings might make to vocabulary learning. We review theory and evidence showing that this is a serious oversight. On...

Monosyllabic Function Words of American English, such as articles (e.g. the, a), pronouns (him, them) and conjunctions (and, or), are notorious for their pronunciation variability in continuous speech. This study explores one potential correlate of this variation: the phonological character of Function Word forms. The Brown Corpus of 1 million words of written text, with each word token labeled...

Two types of consonant gemination characterize Italian: lexical and syntactic. Italian is contrastive, so that two words may differ by only one geminated consonant. In contrast, syntactic occurs across word boundaries, affects the initial a in specific contexts, such as presence monosyllabic morpheme before word. This study investigates acoustic correlates gemination, asking if for are similar ...

The deletion of word-internal alveolar stops in spontaneous English speech is a variation phenomenon that has not previously been investigated. This study quantifies internal deletion statistically using a range of linguistic and extra-linguistic variables, and interprets the results within a model of speech production. Effects were found for speech rate and fluency, word form and word predicta...

The hallmark of skilled reading is the ability to read individual words accurately and quickly in isolation as well as in text, referred to as “context free” word reading skill (Stanovich, 1980). For a skilled reader, even a quick glance at a word activates its pronunciation and meaning. Being able to read words from memory by sight is valuable because it allows readers to focus their attention...

We investigate a generative latent variable model for modelbased word saliency estimation for text modelling and classification. The estimation algorithm derived is able to infer the saliency of words with respect to the mixture modelling objective. We demonstrate experimental results showing that common stop-words as well as other corpus-specific common words are automatically down-weighted an...