103 citations · 232 across the 18 of their papers we have counts for
19 papers
Adapting Self-Supervised Speech Representations for Cross-lingual Dysarthria Detection in Parkinson's Disease
Abner Hernandez, Eunjung Yeo, Kwanghee Choi +12
The limited availability of dysarthric speech data makes cross-lingual detection an important but challenging problem. A key difficulty is that speech representations often encode…
Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages
Chin-Jou Li, Eunjung Yeo, Kwanghee Choi +7
Automatic speech recognition (ASR) for dysarthric speech remains challenging due to data scarcity, particularly in non-English languages. To address this, we fine-tune a voice conv…
A Speech-to-Video Synthesis Approach Using Spatio-Temporal Diffusion for Vocal Tract MRI
Paula Andrea Pérez-Toro, Tomás Arias-Vergara, Fangxu Xing +9
Understanding the relationship between vocal tract motion during speech and the resulting acoustic signal is crucial for aided clinical assessment and developing personalized treat…
Bilingual Dual-Head Deep Model for Parkinson's Disease Detection from Speech
Moreno La Quatra, Juan Rafael Orozco-Arroyave, Marco Sabato Siniscalchi
This work aims to tackle the Parkinson's disease (PD) detection problem from the speech signal in a bilingual setting by proposing an ad-hoc dual-head deep neural architecture for…
Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data
Soroosh Tayebi Arasteh, Mahshad Lotfinia, Paula Andrea Perez-Toro +6
Speech pathology has impacts on communication abilities and quality of life. While deep learning-based models have shown potential in diagnosing these disorders, the use of sensiti…
Exploiting Foundation Models and Speech Enhancement for Parkinson's Disease Detection from Speech in Real-World Operative Conditions
Moreno La Quatra, Maria Francesca Turco, Torbjørn Svendsen +3
This work is concerned with devising a robust Parkinson's (PD) disease detector from speech in real-world operating conditions using (i) foundational models, and (ii) speech enhanc…
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages
Soroosh Tayebi Arasteh, Cristian David Rios-Urrego, Elmar Noeth +4
Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recent…
Representation Learning Strategies to Model Pathological Speech: Effect of Multiple Spectral Resolutions
Gabriel Figueiredo Miller, Juan Camilo Vásquez-Correa, Juan Rafael Orozco-Arroyave +1
This paper considers a representation learning strategy to model speech signals from patients with Parkinson's disease and cleft lip and palate. In particular, it compares differen…
Self-Supervised Speech Representations Preserve Speech Characteristics while Anonymizing Voices
Abner Hernandez, Paula Andrea Pérez-Toro, Juan Camilo Vásquez-Correa +3
Collecting speech data is an important step in training speech recognition systems and other speech-based machine learning models. However, the issue of privacy protection is an in…
Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition
Abner Hernandez, Paula Andrea Pérez-Toro, Elmar Nöth +3
State-of-the-art automatic speech recognition (ASR) systems perform well on healthy speech. However, the performance on impaired speech still remains an issue. The current study ex…
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro +2
Current state of the art acoustic models can easily comprise more than 100 million parameters. This growing complexity demands larger training datasets to maintain a decent general…
The Phonetic Footprint of Parkinson's Disease
Philipp Klumpp, Tomás Arias-Vergara, Juan Camilo Vásquez-Correa +4
As one of the most prevalent neurodegenerative disorders, Parkinson's disease (PD) has a significant impact on the fine motor skills of patients. The complex interplay of different…
Classification of Emotions and Evaluation of Customer Satisfaction from Speech in Real World Acoustic Environments
Luis Felipe Parra-Gallego, Juan Rafael Orozco-Arroyave
This paper focuses on finding suitable features to robustly recognize emotions and evaluate customer satisfaction from speech in real acoustic scenarios. The classification of emot…
Gender Recognition in Informal and Formal Language Scenarios via Transfer Learning
Daniel Escobar-Grisales, Juan Camilo Vasquez-Correa, Juan Rafael Orozco-Arroyave
The interest in demographic information retrieval based on text data has increased in the research community because applications have shown success in different sectors such as se…
Exploring Facial Expressions and Affective Domains for Parkinson Detection
Luis Felipe Gomez-Gomez, Aythami Morales, Julian Fierrez +1
Parkinson's Disease (PD) is a neurological disorder that affects facial movements and non-verbal communication. Patients with PD present a reduction in facial movements called hypo…
Comparison of user models based on GMM-UBM and i-vectors for speech, handwriting, and gait assessment of Parkinson's disease patients
J. C. Vasquez-Correa, T. Bocklet, J. R. Orozco-Arroyave +1
Parkinson's disease is a neurodegenerative disorder characterized by the presence of different motor impairments. Information from speech, handwriting, and gait signals have been c…
Analysis and Evaluation of Handwriting in Patients with Parkinson's Disease Using kinematic, Geometrical, and Non-linear Features
C. D. Rios-Urrego, J. C. Vásquez-Correa, J. F. Vargas-Bonilla +3
Background and objectives: Parkinson's disease is a neurological disorder that affects the motor system producing lack of coordination, resting tremor, and rigidity. Impairments in…
Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson's Disease from Speech in Three Different Languages
J. C. Vásquez-Correa, T. Arias-Vergara, C. D. Rios-Urrego +4
Parkinson's disease patients develop different speech impairments that affect their communication capabilities. The automatic assessment of the speech of the patients allows the de…
Characterization of the Handwriting Skills as a Biomarker for Parkinson Disease
R. Castrillon, A. Acien, J. R. Orozco-Arroyave +6
In this paper we evaluate the suitability of handwriting patterns as potential biomarkers to model Parkinson disease (PD). Although the study of PD is attracting the interest of ma…