4 accepted papers
Despite the promising performance of state-of-the-art approaches for Parkinson’s Disease (PD) detection, these approaches often analyze individual speech segments in isolation, which can lead to sub-optimal results. Dysarthric cues that characterize speech impairments from PD patients are expected t…
Low-rank adaptation (LoRA) is a widely used method for parameter-efficient finetuning. However, existing LoRA variants lack mechanisms to explicitly disambiguate task-relevant information within the learned low-rank subspace, potentially limiting downstream performance. We propose Factorized Variat…
Recently proposed automatic pathological speech detection approaches rely on spectrogram input representations or wav2vec2 embeddings. These representations may contain pathology-irrelevant uncorrelated information, such as changing phonetic content or variations in speaking style across time, which…
We present a novel multiview canonical correlation analysis model based on a variational approach. This is the first nonlinear model that takes into account the available graph-based geometric constraints while being scalable for processing large scale datasets with multiple views. It is based on an…