3 citations · 3 across the 15 of their papers we have counts for
6 papers · 1 filter
DNSMOS-C: Improving End-to-end Speech Quality Models via Contrastive Learning
Xinyu Liang, Fredrik Cumlin, Victor Ungureanu +3
We introduce DNSMOS-C, a compact end-to-end speech quality assessment model that extends the DNSMOS Pro framework by integrating a MOS-guided triplet-based contrastive loss. Applie…
Generative Modeling for Physiological Signals
Xinqi Bao, Ernest Kamavuako, Saikat Chatterjee
Physiological signals support clinical diagnosis, health monitoring, rehabilitation, wearable sensing, and human--machine interaction. However, their applications are often constra…
Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
Xinqi Bao, Jia Bi, Xin Chen +2
Publicly available phonocardiogram (PCG) datasets remain limited in size and pathological diversity, constraining both auscultation training and the generalisation of automated hea…
SA-SSL-MOS: Self-supervised Learning MOS Prediction with Spectral Augmentation for Generalized Multi-Rate Speech Assessment
Fengyuan Cao, Xinyu Liang, Fredrik Cumlin +4
Designing a speech quality assessment (SQA) system for estimating mean-opinion-score (MOS) of multi-rate speech with varying sampling frequency (16-48 kHz) is a challenging task. T…
DNS: Data-driven Nonlinear Smoother for Complex Model-free Process
Fredrik Cumlin, Anubhab Ghosh, Saikat Chatterjee
We propose data-driven nonlinear smoother (DNS) to estimate a hidden state sequence of a complex dynamical process from a noisy, linear measurement sequence. The dynamical process…
VSE: Variational state estimation of complex model-free process
Gustav Norén, Anubhab Ghosh, Fredrik Cumlin +1
We design a variational state estimation (VSE) method that provides a closed-form Gaussian posterior of an underlying complex dynamical process from (noisy) nonlinear measurements.…