Publications

(2021). On Modeling Glottal Source Information for Phonation Assessment in Parkinson’s Disease. 21st Annual Conference of the International Speech Communication Association.

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(2021). Influence of the Interviewer on the Automatic Assessment of Alzheimer's Disease in the Context of the ADReSSo Challenge.. 21st Interspeech.

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(2020). Parallel Representation Learning for the Classification of Pathological Speech: Studies on Parkinson’s Disease and Cleft Lip and Palate. Speech Communication.

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(2020). Multi-channel spectrograms for speech processing applications using deep learning methods. Pattern Analysis and Applications.

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(2020). Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease. Neurological Disorders and Imaging Physics, Volume 5.

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(2020). Automatic detection of Voice Onset Time in voiceless plosives using gated recurrent units. Digital Signal Processing.

(2020). Nonlinear dynamics and Poincaré sections to model gait impairments in different stages of Parkinson’s disease. Nonlinear Dynamics.

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(2020). Comparison of User Models Based on GMM-UBM and I-Vectors for Speech, Handwriting, and Gait Assessment of Parkinson’s Disease Patients. 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2020). Word-Embeddings and Grammar Features to Detect Language Disorders in Alzheimer’s Disease Patients. TecnoLógicas.

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(2020). Identity Verification in Virtual Education Using Biometric Analysis Based on Keystroke Dynamics. TecnoLógicas.

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(2020). Apkinson: the smartphone application for telemonitoring Parkinson’s patients through speech, gait and hands movement. Neurodegenerative Disease Management.

(2019). Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users. Iberoamerican Congress on Pattern Recognition (CIARP).

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(2019). Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson’s Disease from Speech in Three Different Languages. Iberoamerican Congress on Pattern Recognition (CIARP).

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(2019). Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson's Disease Patients. Iberoamerican Congress on Pattern Recognition (CIARP).

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(2019). Feature Representation of Pathophysiology of Parkinsonian Dysarthria. Twentieth Annual Conference of the International Speech Communication Association.

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(2019). Natural Language Analysis to Detect Parkinson's Disease. International Conference on Text, Speech, and Dialogue.

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(2019). Surgical mask detection with deep recurrent phonetic models. Twentyfirst Annual Conference of the International Speech Communication Association.

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(2019). Phonet: A Tool Based on Gated Recurrent Neural Networks to Extract Phonological Posteriors from Speech. Twentieth Annual Conference of the International Speech Communication Association.

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(2019). Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data. Twentieth Annual Conference of the International Speech Communication Association.

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(2019). Speech differences between CI users with pre-and postlingual onset of deafness detected by speech processing methods on voiceless to voice transitions. Laryngo-Rhino-Otologie.

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(2019). Automated Cross-language Intelligibility Analysis of Parkinson’s Disease Patients Using Speech Recognition Technologies. Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL): Student Research Workshop.

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(2019). Analysis and evaluation of handwriting in patients with Parkinson’s disease using kinematic, geometrical, and non-linear features. Computer methods and programs in biomedicine.

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(2018). Unobtrusive Monitoring of Speech Impairments of Parkinson's Disease Patients Through Mobile Devices. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2018). Towards an automatic evaluation of the dysarthria level of patients with Parkinson's disease. Journal of communication disorders.

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(2018). Speaker models for monitoring Parkinson’s disease progression considering different communication channels and acoustic conditions. Speech Communication.

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(2018). Representaciones tiempo-frecuencia basadas en sensores inerciales para caracterizar la marcha en la enfermedad de Parkinson. TecnoLógicas.

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(2018). Phonological i-Vectors to Detect Parkinson's Disease. International Conference on Text, Speech, and Dialogue.

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(2018). NeuroSpeech: An open-source software for Parkinson's speech analysis. Digital Signal Processing.

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(2018). Multimodal I-vectors to Detect and Evaluate Parkinson's Disease. Proc. Interspeech 2018.

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(2018). Multimodal assessment of Parkinson's disease: a deep learning approach. IEEE journal of biomedical and health informatics.

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(2018). Automatic Intelligibility Assessment of Parkinson's Disease with Diadochokinetic Exercises. Workshop on Engineering Applications.

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(2018). Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson's Disease. Twentieth Annual Conference of the International Speech Communication Association.

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(2018). A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson’s Disease. Workshop on Engineering Applications.

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(2018). A Multitask Learning Approach to Assess the Dysarthria Severity in Patients with Parkinson's Disease. Nineteenth Annual Conference of the International Speech Communication Association.

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(2017). Speaker Model to Monitor the Neurological State and the Dysarthria Level of Patients with Parkinson’s Disease. International Conference on Text, Speech, and Dialogue.

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(2017). Phonation and Articulation Analyses in Laryngeal Pathologies, Cleft Lip and Palate, and Parkinson’s Disease. International Work-Conference on the Interplay Between Natural and Artificial Computation.

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(2017). Parkinson's disease and aging: analysis of their effect in phonation and articulation of speech. Cognitive Computation.

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(2017). On the impact of non-modal phonation on phonological features. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2017). Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2017). Language independent assessment of motor impairments of patients with Parkinson’s disease using i-vectors. International Conference on Text, Speech, and Dialogue.

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(2017). Effect of acoustic conditions on algorithms to detect Parkinson's disease from speech. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2017). Convolutional Neural Network to Model Articulation Impairments in Patients with Parkinson's Disease.. Eighteenth Annual Conference of the International Speech Communication Association.

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(2017). Characterisation of voice quality of Parkinson’s disease using differential phonological posterior features. Computer Speech & Language.

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(2017). Apkinson-A Mobile Monitoring Solution for Parkinson's Disease.. Eighteenth Annual Conference of the International Speech Communication Association.

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(2016). Word accuracy and dynamic time warping to assess intelligibility deficits in patients with parkinsons disease. 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA).

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(2016). Wavelet-based time-frequency representations for automatic recognition of emotions from speech. Speech Communication; 12. ITG Symposium.

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(2016). Towards an automatic monitoring of the neurological state of Parkinson's patients from speech. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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(2016). Parkinson's Disease Progression Assessment from Speech Using GMM-UBM.. 17th Annual Conference of the International Speech Communication Association (INTERSPEECH).

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(2016). Non-linear dynamics characterization from wavelet packet transform for automatic recognition of emotional speech. Recent Advances in Nonlinear Speech Processing.

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(2016). Gender-dependent gmm-ubm for tracking parkinson's disease progression from speech. Speech Communication; 12. ITG Symposium.

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(2016). Emotion recognition from speech with acoustic, non-linear and wavelet-based features extracted in different acoustic conditions. Master thesis, Faculty of Engineering, University of Antioquia.

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(2016). Automatic detection of hypernasal speech of children with cleft lip and palate from spanish vowels and words using classical measures and nonlinear analysis. Revista Facultad de Ingenierı́a Universidad de Antioquia.

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(2015). Time dependent ARMA for automatic recognition of fear-type emotions in speech. International Conference on Text, Speech, and Dialogue.

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(2015). Emotion recognition from speech under environmental noise conditions using wavelet decomposition. 2015 International Carnahan Conference on Security Technology (ICCST).

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(2015). Automatic emotion recognition in compressed speech using acoustic and non-linear features. 2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA).

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(2015). Automatic detection of Parkinson's disease from continuous speech recorded in non-controlled noise conditions. Sixteenth Annual Conference of the International Speech Communication Association.

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(2014). New computer aided device for real time analysis of speech of people with Parkinson's disease. Revista Facultad de Ingenieria Universidad de Antioquia.

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(2014). Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals. 2014 International Carnahan Conference on Security Technology (ICCST).

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(2014). Evaluation of the effects of speech enhancement algorithms on the detection of fundamental frequency of speech. 2014 XIX Symposium on Image, Signal Processing and Artificial Vision.

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(2013). Design and implementation of an embedded system for real time analysis of speech from people with parkinson's disease. Symposium of Signals, Images and Artificial Vision-2013: STSIVA-2013.