NeuroSpeech

NeuroSpeech is a software for modeling pathological speech signals considering different speech dimensions: phonation, articulation, prosody, and intelligibility. Although it was developed to model dysarthric speech signals from Parkinson's patients, its structure allows other computer scientists or developers to include other pathologies and/or measures. Different tasks can be performed: (1) modeling of the signals considering the aforementioned speech dimensions, (2) automatic discrimination of Parkinson's vs. non-Parkinson's, and (3) prediction of the neurological state according to the Unified Parkinson's Disease Rating Scale (UPDRS) score. The prediction of the dysarthria level according to the Frenchay Dysarthria Assessment scale is also provided

Multi-view representation learning via gcca for multimodal analysis of Parkinson's disease

Information from different bio-signals such as speech, handwriting, and gait have been used to monitor the state of Parkinson's disease (PD) patients, however, all the multimodal bio-signals may not always be available. We propose a method based on multi-view representation learning via generalized canonical correlation analysis (GCCA) for learning a representation of features extracted from handwriting and gait that can be used as a complement to speech-based features. Three different problems are addressed: classification of PD patients vs. healthy controls, prediction of the neurological state of PD patients according to the UPDRS score, and the prediction of a modified version of the Frenchay dysarthria assessment (m-FDA). According to the results, the proposed approach is suitable to improve the results in the addressed problems, specially in the prediction of the UPDRS, and m-FDA scores

A standard protocol to report discrete stage‐structured demographic information

Stage-based demographic methods, such as matrix population models (MPMs), are powerful tools used to address a broad range of fundamental questions in ecology, evolutionary biology and conservation science. Accordingly, MPMs now exist for over 3000 species worldwide. These data are being digitised as an ongoing process and periodically released into two large open-access online repositories: the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. During the last decade, data archiving and curation of COMPADRE and COMADRE, and subsequent comparative research, have revealed pronounced variation in how MPMs are parameterized and reported. Here, we summarise current issues related to the parameterisation and reporting of MPMs that arise most frequently and outline how they affect MPM construction, analysis, and interpretation. To quantify variation in how MPMs are reported, we present results from a survey identifying key aspects of MPMs that are frequently unreported in manuscripts. We then screen COMPADRE and COMADRE to quantify how often key pieces of information are omitted from manuscripts using MPMs. Over 80% of surveyed researchers (n = 60) state a clear benefit to adopting more standardised methodologies for reporting MPMs. Furthermore, over 85% of the 300 MPMs assessed from COMPADRE and COMADRE omitted one or more elements that are key to their accurate interpretation. Based on these insights, we identify fundamental issues that can arise from MPM construction and communication and provide suggestions to improve clarity, reproducibility and future research utilising MPMs and their required metadata. To fortify reproducibility and empower researchers to take full advantage of their demographic data, we introduce a standardised protocol to present MPMs in publications. This standard is linked to www.compadre-db.org, so that authors wishing to archive their MPMs can do so prior to submission of publications, following examples from other open-access repositories such as DRYAD, Figshare and Zenodo. Combining and standardising MPMs parameterized from populations around the globe and across the tree of life opens up powerful research opportunities in evolutionary biology, ecology and conservation research. However, this potential can only be fully realised by adopting standardised methods to ensure reproducibility

NeuroSpeech: An open-source software for Parkinson's speech analysis

A new software for modeling pathological speech signals is presented in this paper. The software is called NeuroSpeech. This software enables the analysis of pathological speech signals considering different speech dimensions: phonation, articulation, prosody, and intelligibility. All the methods considered in the software have been validated in previous experiments and publications. The current version of NeuroSpeech was developed to model dysarthric speech signals from people with Parkinson's disease; however, the structure of the software allows other computer scientists or developers to include other pathologies and/or other measures in order to complement the existing options. Three different tasks can be performed with the current version of the software: (1) the modeling of the speech recordings considering the aforementioned speech dimensions, (2) the automatic discrimination of Parkinson's vs. non-Parkinson's speech signals (if the user has access to recordings of other pathologies, he/she can re-train the system to perform the detection of other diseases), and (3) the prediction of the neurological state of the patient according to the Unified Parkinson's Disease Rating Scale (UPDRS) score. The prediction of the dysarthria level according to the Frenchay Dysarthria Assessment scale is also provided (the user can also train the system to perform the prediction of other kind of scales or degrees of severity).To the best of our knowledge, this is the first software with the characteristics described above, and we consider that it will help other researchers to contribute to the state-of-the-art in pathological speech assessment from different perspectives, e.g., from the clinical point of view for interpretation, and from the computer science point of view enabling the test of different measures and pattern recognition techniques

A standard protocol to report discrete stage-structured demographic information

Funder: Maria Zambrano Next Generation EU FellowshipAbstract Stage‐based demographic methods, such as matrix population models (MPMs), are powerful tools used to address a broad range of fundamental questions in ecology, evolutionary biology and conservation science. Accordingly, MPMs now exist for over 3000 species worldwide. These data are being digitised as an ongoing process and periodically released into two large open‐access online repositories: the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. During the last decade, data archiving and curation of COMPADRE and COMADRE, and subsequent comparative research, have revealed pronounced variation in how MPMs are parameterized and reported. Here, we summarise current issues related to the parameterisation and reporting of MPMs that arise most frequently and outline how they affect MPM construction, analysis, and interpretation. To quantify variation in how MPMs are reported, we present results from a survey identifying key aspects of MPMs that are frequently unreported in manuscripts. We then screen COMPADRE and COMADRE to quantify how often key pieces of information are omitted from manuscripts using MPMs. Over 80% of surveyed researchers (n = 60) state a clear benefit to adopting more standardised methodologies for reporting MPMs. Furthermore, over 85% of the 300 MPMs assessed from COMPADRE and COMADRE omitted one or more elements that are key to their accurate interpretation. Based on these insights, we identify fundamental issues that can arise from MPM construction and communication and provide suggestions to improve clarity, reproducibility and future research utilising MPMs and their required metadata. To fortify reproducibility and empower researchers to take full advantage of their demographic data, we introduce a standardised protocol to present MPMs in publications. This standard is linked to www.compadre‐db.org, so that authors wishing to archive their MPMs can do so prior to submission of publications, following examples from other open‐access repositories such as DRYAD, Figshare and Zenodo. Combining and standardising MPMs parameterized from populations around the globe and across the tree of life opens up powerful research opportunities in evolutionary biology, ecology and conservation research. However, this potential can only be fully realised by adopting standardised methods to ensure reproducibility. </jats:p