1 citations · 1 across the 3 of their papers we have counts for
7 papers
Detecting Neurodegenerative Diseases using Frame-Level Handwriting Embeddings
Sarah Laouedj, Yuzhe Wang, Jesus Villalba +3
In this study, we explored the use of spectrograms to represent handwriting signals for assessing neurodegenerative diseases, including 42 healthy controls (CTL), 35 subjects with…
Unsupervised Speech Segmentation and Variable Rate Representation Learning using Segmental Contrastive Predictive Coding
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Typically, unsupervised segmentation of speech into the phone and word-like units are treated as separate tasks and are often done via different methods which do not fully leverage…
Beyond Isolated Utterances: Conversational Emotion Recognition
Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2
Speech emotion recognition is the task of recognizing the speaker's emotional state given a recording of their utterance. While most of the current approaches focus on inferring em…
Pathological voice adaptation with autoencoder-based voice conversion
Marc Illa, Bence Mark Halpern, Rob van Son +2
In this paper, we propose a new approach to pathological speech synthesis. Instead of using healthy speech as a source, we customise an existing pathological speech sample to a new…
Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Automatic detection of phoneme or word-like units is one of the core objectives in zero-resource speech processing. Recent attempts employ self-supervised training methods, such as…
Artificial Intelligence applied to chest X-Ray images for the automatic detection of COVID-19. A thoughtful evaluation approach
Julian D. Arias-Londoño, Jorge A. Gomez-Garcia, Laureano Moro-Velazquez +1
Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ray. The combined analysis aims…