Download Computational Processing of the Portuguese Language: 11th by Jorge Baptista PDF

By Jorge Baptista

This booklet constitutes the refereed court cases of the eleventh overseas Workshop on Computational Processing of the Portuguese Language, PROPOR 2014, held in Sao Carlos, Brazil, in October 2014. The 14 complete papers and 19 brief papers awarded during this quantity have been rigorously reviewed and chosen from sixty three submissions. The papers are equipped in topical sections named: speech language processing and purposes; linguistic description, syntax and parsing; ontologies, semantics and lexicography; corpora and language assets and normal language processing, instruments and applications.

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Additional info for Computational Processing of the Portuguese Language: 11th International Conference, PROPOR 2014, São Carlos/SP, Brazil, October 6-8, 2014. Proceedings

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The set of statistic functionals applied to the LLD contours at the utterance level includes percentiles, modulations, moments, peaks and regressions, and is presented in Table 5. The LLDs and functionals are described in detail in [27]. In an attempt to preserve the features that are the most relevant to the task at hand and to reduce the complexity of the classification stage, we applied a correlationbased feature subset selection evaluator with a best-first search method [28]. This is a supervised dimensionality reduction technique that evaluates the worth of a subset of features by considering their individual predictive ability along with the degree of redundancy between features.

It is a simple classifier that does not require an elaborate tuning scheme, and we found it appropriate for a scenario such as ours with a low number of subjects. Every attribute was calculated per speaker, thus resulting in 29 instances to be classified. To deal with the unbalanced dataset (groups with different number of speakers) we use the Synthetic Minority Oversampling Technique [30] to oversample the minority class. The tests and dataset manipulation were carried out by WEKA data mining toolkit [31] for data separations A and B.

Parkinson disease speech corpus represents 90 minutes of read speech recorded at a 48 kHz sampling rate. A healthy control group (3 females and 4 males between 25 and 51 years old) was also recruited for recording the same battery of speech production tasks under identical acoustic conditions. Segmentation at the phone-level was automatically done for each session through forced-alignment with a phone recognizer [19]. This process was further manually verified. The H-Y stages of the patients are not very distinct, but it is possible to differentiate two PD speech subtypes on the basis on the fluency of the speech produced: normally articulated and rhythmical (named here as Low-PD), and slow and abnormally articulated speech (named here as High-PD).

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