308 citations · 410 across the 11 of their papers we have counts for
6 papers · 1 filter
ClosureBench: A Constructive Benchmark for Compositional Graph Reasoning
Stefano Goria
Large language models fail on multi-step compositional reasoning, but measuring that failure is hard, because new models are trained on the benchmarks used to evaluate them. A fixe…
Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning
Roseline Polle, Owen Parsons, George Fairs +5
Synthetic data augmentation in speech is common practice for linguistic tasks like ASR, but has seen far less work for paralinguistic ones, especially clinical tasks where labelled…
A multimodal Bayesian Network for symptom-level depression and anxiety prediction from voice and speech data
Agnes Norbury, George Fairs, Alexandra L. Georgescu +3
During psychiatric assessment, clinicians observe not only what patients report, but important nonverbal signs such as tone, speech rate, fluency, responsiveness, and body language…
Random-Bridges as Stochastic Transports for Generative Models
Stefano Goria, Levent A. Mengütürk, Murat C. Mengütürk +1
This paper motivates the use of random-bridges -- stochastic processes conditioned to take target distributions at fixed timepoints -- in the realm of generative modelling. Herein,…
Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models
Roseline Polle, Agnes Norbury, Alexandra Livia Georgescu +2
Speaker-dependent modelling can substantially improve performance in speech-based health monitoring applications. While mixed-effect models are commonly used for such speaker adapt…
Bayesian Networks for the robust and unbiased prediction of depression and its symptoms utilizing speech and multimodal data
Salvatore Fara, Orlaith Hickey, Alexandra Georgescu +3
Predicting the presence of major depressive disorder (MDD) using behavioural and cognitive signals is a highly non-trivial task. The heterogeneous clinical profile of MDD means tha…