The NIST 2011 Language Recognition Evaluation focuses on language pair discrimination for 24 languages/dialects, some of which may be considered mutually intelligible or closely related. The LRE11 evaluation required new data for all languages, comprising both conversational telephone speech and broadcast narrowband speech from multiple sources in each language. Given the potential confusion am...

OBJECTIVES Most Campylobacter cases are treated as low risk enterics (LRE) and receive a mailed letter from Toronto Public Health (TPH) with a questionnaire to gather basic risk information. This study sought to identify reasons why Campylobacter cases who were sent this questionnaire did not respond to the letter and to determine whether any of these cases were working in a high-risk occupatio...

We propose a novel design for acoustic feature-based automatic spoken language recognizers. Our design is inspired by recent advances in text-independent speaker recognition, where intraclass variability is modeled by factor analysis in Gaussian mixture model (GMM) space. We use approximations to GMMlikelihoods which allow variable-length data sequences to be represented as statistics of fixed ...

Based on the conventional score calibration techniques with gaussian backend and logistic regression of the relative likelihood scores, this paper proposes a method of score calibration specific to a subset of related languages. Detection scores to two related languages are considered as two sources with similar and complementary information. In the proposed score calibration, an optimal linear...

The aim of this work is to develop ajlexible and eficient approach to the classifcation of the ratio of voiced to unvoiced excitation sources in continuous speech. To achieve this aim we adopt a probabilistic neural network approach. This is accomplished by designing a multi layer perceptron classifer trained by steepest descent minimization of the Least Relative Entropy W) cost function. By us...

Phonotactic language recognition is one of major techniques used for automatic recognition of spoken languages. We propose a feature extraction technique based on PCA to be used with SVM-based systems. This technique improves speed of the training, in some cases more than 1000 times, allowing systems to be effectively trained on much larger data sets. Speed-up of the test phase can be even grea...