![]() ![]() We collected sustained phonations from 31 people, 23 with PD. We introduce a new measure of dysphonia, pitch period entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. This study demonstrates that data-driven methods-commonplace in studies of human neuroanatomy and functional connectivity-provide a powerful and efficient means for mapping functional representations in the brain.read more read lessĪbstract: In this paper, we present an assessment of the practical value of existing traditional and nonstandard measures for discriminating healthy people from people with Parkinson's disease (PD) by detecting dysphonia. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. We then use a novel generative model to create a detailed semantic atlas. We show that the semantic system is organized into intricate patterns that seem to be consistent across individuals. Here we systematically map semantic selectivity across the cortex using voxel-wise modelling of functional MRI (fMRI) data collected while subjects listened to hours of narrative stories. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. read more read lessĪbstract: The meaning of language is represented in regions of the cerebral cortex collectively known as the 'semantic system'. Numeric compatibility with future versions is ensured by means of unit tests. It supports on-line incremental processing for all implemented features as well as off-line and batch processing. It is fast, runs on Unix and Windows platforms, and has a modular, component based architecture which makes extensions via plug-ins easy. openSMILE is implemented in C++ with no third-party dependencies for the core functionality. Delta regression and various statistical functionals can be applied to the low-level descriptors. Audio low-level descriptors such as CHROMA and CENS features, loudness, Mel-frequency cepstral coefficients, perceptual linear predictive cepstral coefficients, linear predictive coefficients, line spectral frequencies, fundamental frequency, and formant frequencies are supported. I'm still revising the document's text to reflect a multi-author collaborative environment, but you will be duly credited for your work.įinally, although pull requests are welcome, I reserve the right to modify, revise, or reject any requests for any reasons I see fit.Abstract: We introduce the openSMILE feature extraction toolkit, which unites feature extraction algorithms from the speech processing and the Music Information Retrieval communities. Any text and figures should feature only your own work (or properly cited quotes of others' work), and by contributing, you assert that your contributions will fall under the document's Creative Commons license. ![]() If you'd like to make a more substantial contribution, please feel free to revise both the usingpraat.md, usingpraat.bib, and to add any additional figures to build. If you find a typo, formatting issue, or other problem in the document, please feel free to submit a pull request which makes the change, following the formatting guidelines above. This assumes you have a working Unix environment, which you really should :)Īfter some chugging, it will render the latest document. To render this document from the source, clone this repository, make sure you have (minimally) XeLaTeX, Bibtex, pandoc and perl around, and then run bash render_using_praat.sh on your local machine. In general, your contribution text should use Markdown, and rely on TeX only for citations, figures, and references.Īll figures are in the 'build' folder, and all bibliographic information is in 'usingpraat.bib'. The bulk of the text is written in Markdown, but complex formatting, tables, and references are rendered in LaTeX. This is a hybrid XeLaTeX/Markdown document, with the main document being usingpraat.md. About the documentįor more details on the resource, as well as some accompanying materials, go to. This is the official Github page for the Open Educational Resource 'Using Praat for Linguistic Research', written by Will Styler. ![]()
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