A query speller is crucial to search engine in improving web search relevance. This paper describes novel methods for use of distributional similarity estimated from query logs in learning improved query spelling correction models. The key to our methods is the property of distributional similarity between two terms: it is high between a frequently occurring misspelling and its correction, and ...

This work introduces a novel classifier for a P300-based speller, which, contrary to common methods, can be trained entirely unsupervisedly using an Expectation Maximization approach, eliminating the need for costly dataset collection or tedious calibration sessions. We use publicly available datasets for validation of our method and show that our unsupervised classifier performs competitively ...

This well-known manual has provided a useful guide for those who have to administer the workings of the Mental Health Act. In this edition, it has been brought up-to-date and given a more attractive appearance. Various chapters deal with admission of patients to hospital, guardianship, discharge, private nursing homes, the courts, review tribunals and care of patients' property. There are also ...

The paper describes a morphological analyser for Estonian and how using a text corpus influenced the process of creating it and the resulting program itself. The influence is not limited with the lexicon only, but is noticeable in the resulting algorithm and implementation too. When work on the analyser started, there was no computational treatment of Estonian derivatives and compounds. After s...

A brain-computer interface (BCI) is a communication system that allows to control a computer or any other device thanks to the brain activity. The BCI described in this paper is based on the P300 speller BCI paradigm introduced by Farwell and Donchin . An unsupervised algorithm is proposed to enhance P300 evoked potentials by estimating spatial filters; the raw EEG signals are then projected in...

We consider an EEG-based, wireless braincomputer interface (BCI) with which subjects can “mind spell” text on a computer screen. The application is based on the detection of the P300 event-related potential (ERP). The frequency range for preprocessing the EEG recordings, and the location and length of the time interval after stimulus onset, are selected with respect to the classification accura...

Most of the previous work on brain-computer interfaces (BCIs) exploiting the P300 in electroencephalography (EEG) has focused on low-level signal processing algorithms such as feature extraction and classification methods. Although a significant improvement has been made in the past, the accuracy of detecting P300 is limited by the inherently low signal-to-noise ratio in EEGs. In this paper, we...

Brain-computer interfaces (BCI) enable non-muscular powerful channel for communicating thanks to direct communication between the user’s brain and a computer. In this article, the presented BCI concerns the P300 speller which enables people to write a text on a computer by estimating P300 evoked potentials. In this work, an unsupervised algorithm is introduced for signal subspace estimation: th...

In this paper, we propose a classification algorithm for P300-based Brain Computer Interface (BCI). Brain Computer Interface (BCI) with P300 speller helps Amyotrophic Lateral Sclerosis (ALS) patients to spell words with the help of their brain signal activities. Amyotrophic Lateral Sclerosis (ALS) also known as Lou Gehrig's disease in which certain nerve cells in brain and spinal cord also call...

abstract brian computer interface (bci) is a direct communication pathway between the brain and an external device. bcis are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. in this work a new algorithm is introduced to enhancing eeg signals that have been concerned the p300 problem. signal to noise ratio of eeg signals is very low and have  much art...