We describe and motivate an unsupervised lexical error detection and correction algorithm and its application in a tool called Lexbar appearing as a query box on the Web browser toolbar or as a search engine interface. Lexbar accepts as user input candidate strings of English to be checked for acceptability and, where errors are detected, offers corrections. We introduce the notion of hybrid n-...

Objectives: Sentence repetition tasks (SRTs) are clinically useful for examining working memory ability and discriminating residual language delay. This study aims to examine sentence skills by groups of children with SSDs analyze error types morphosyntactic strengths weaknesses in SRTs. Methods: Thirty-four aged 5-7 years were classified into articulation disorders, phonological delays, disord...

We describe MH who presents with agrammatic aphasia and anomia, and who produces semantic errors in the absence of a central semantic impairment. This pattern of performance implies damage to syntactic processes operating between semantics and phonological output. Damage here may lead to lexical selection errors and a deficit in combining words to form phrases. We investigated MH's knowledge an...

This research aims at exploring in an irregular orthographic system like French, if spelling is related to written composition. French particularly interesting because it includes phonographic irregularities (i.e., inconsistencies), lexical difficulties and numerous morphological silent marks (e.g., plural noun, adjective, verb agreement). In a longitudinal study from the beginning of Grade 3 e...

An automatic system for detection of pronunciation errors by adult learners of English is embedded in a language–learning package. Four main features are: (1) a recognizer robust to non–native speech; (2) localization of phone– and word–level errors; (3) diagnosis of what sorts of phone–level errors took place; and (4) a lexical– stress detector. These tools together allow robust, consistent, a...

In this work, we examine and attempt to extend the coverage of a German HPSG grammar. We use the grammar to parse a corpus of newspaper text and evaluate the proportion of sentences which have a correct attested parse, and analyse the cause of errors in terms of lexical or constructional gaps which prevent parsing. Then, using a maximum entropy model, we evaluate prediction of lexical types in ...

In this research we aim to detect subjective sentences in spontaneous speech and label them for polarity. We introduce a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-grams with varying levels of lexical instantiation. Applying this technique to meeting speech, we gain significant improvement over state-of-theart approaches and demonstrate...

A method for learning lexical representations of unknown words in an unsupervised manner is described. The unknown words are automatically extracted from continuous speech and a clustering algorithm is used to derive word clusters and lexical representations based on the set of phonetic units used in the system. In experiments, we verify the robustness of the approach. An interesting feature is...

We present a novel approach to lexical error recovery on textual input. An advanced robust tokenizer has been implemented that can not only correct spelling mistakes, but also recover from segmentation errors. Apart from the orthographic considerations taken, the tokenizer also makes use of linguistic expectations extracted from a training corpus. The idea is to arrange Hidden Markov Models (HM...