We present a study which is concerned with word recognition rates for heavily degraded documents. We compare human with machine reading capabilities in a series of experiments, which explores the interaction of word/non-word recognition, word frequency and legality of non-words with degradation level. We also study the innuence of character segmentation, and compare human performance with that ...

Adult word recognition is influenced by prior exposure to phonologically or semantically related words (cup primes cat or plate) compared to unrelated words (door), suggesting that words are organised in the adult lexicon based on their phonological and semantic properties and that word recognition implicates not just the heard word, but also related words. We investigate the phonological organ...

A new psycholinguistically motivated and neural network based model of human word recognition is presented. In contrast to earlier models it uses real speech as input. At the word layer acoustical and temporal information is stored by sequences of connected sensory neurons which pass on sensor potentials to a word neuron. In experiments with a small lexicon which includes groups of very similar...

We present a study which is concerned with word recognition rates for heavily degraded documents. We compare human with machine reading capabilities in a series of experiments, which explores the interaction of word/non-word recognition, word frequency and legality of non-words with degradation level. We also study the influence of character segmentation, and compare human performance with that...

Visual world studies show that upon hearing a word in target-absent visual context containing related and unrelated items, toddlers adults briefly direct their gaze toward phonologically before shifting semantically visually ones. We present neural network model processes dynamic unfolding phonological representations of words maps them to static internal lexical, semantic, representations. The...

Single word recognition experiments have shown that when a word is primed by an orthographic neighbour (e.g. blur primed by blue), reaction times to the target increase (e.g., Davis & Lupker, 2006; De Moor & Brysbaert, 2000; Drews & Zwitserlood, 1995; Nakayama et al., 2008). Models of word recognition like the Interactive Activation (IA) model (McClelland & Rumelhart, 1981) and the SOLAR model ...

A computational model for the recognition of multi-font machine-printed word images of highly variable quality is given. The model integrates three word recognition algorithms, each of which utilizes a diierent form of shape and context information. The approaches are character recognition based, segmentation based, and word-shape analysis based. The model overcomes limitations of previous solu...

Abstract We propose a method of dynamically registering out-of-vocabulary (OOV) words by assigning the pronunciations these to pre-inserted OOV tokens, editing tokens. To do this, we add tokens an additional, partial copy our corpus, either randomly or part-of-speech (POS) tags in selected utterances, when training language model (LM) for speech recognition. This results LM containing which can...