The extent to which language learners hear non-native sounds in terms of native categories depends in part on acoustic and auditory similarities between the two sets of sounds. One unresolved issue is the choice of parameter space in which similarity should be measured. The current paper demonstrates the application of an unsupervised, corpusbased, data-driven mapping technique which permits th...

This paper compares the performance of topographic analysis and binary analysis for recognition of digits in hydrographic maps. The performance of each method was measured by the correct classification rate of the final symbol recognition step when processing a complete hydrographic map of size 0.45× 0.6m with about 35,000 digits. The experimental results indicated that binary analysis had a be...

This paper is a discussion on the practical issues faced by Information Systems professionals when they employ Grounded Theory Method (GTM) in Information Systems research. Various strands of GTM are in us, all of which are derivates of the grand GTM proposed by Barney G. Glaser and Anselm G. Strauss in 1967. Starting with the dicta proposed by these two authors in 1967 on the use of GTM, the p...

Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the use of tools such as regularization from the theory of (supervised) risk minimization for unsupervised settings. Moreover, this setting is very closely related to both principal curves and the generative topographic map...

It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs fail to capture trajectory information in the acoustic signal. This paper introduces Gaussian Transition Models (GTM) to model trajectories implicitly. Comparing to alternative approaches, such as segment modeling and ...

In this paper we compare the accuracy of a range of advanced density models for gas identification from sensor array signals. Density estimation is applied in the construction of classifiers through the use of Bayes rule. Experiments on real sensors data proved the effectiveness of the approach with an excellent classification performance. We compare the classification accuracy of four density ...

Many settings of unsupervised learning can be viewed as quantization problems | the minimization of the expected quantization error subject to some restrictions. This allows the use of tools such as regularization from the theory of (supervised) risk minimization for unsupervised settings. This setting turns out to be closely related to principal curves, the generative topographic map, and robu...

In this paper, we present the systems developed by GTMUVigo team for the query by example search on speech task (QUESST) at MediaEval 2015. The systems consist in a fusion of 11 dynamic time warping based systems that use phoneme posteriorgrams for speech representation; the primary system introduces a technique to select the most relevant phonetic units on each phoneme decoder, leading to an i...

We used fMRI at 3 Tesla and improved spatial resolution (2 x 2 x 2 mm(3)) to investigate topographic organization in human frontal cortex using memory-guided response tasks performed at 8 or 12 peripheral locations arranged clockwise around a central fixation point. The tasks required the location of a peripheral target to be remembered for several seconds after which the subjects either made a...