308 citations · 410 across the 11 of their papers we have counts for
11 papers
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…
Path Signature Representation of Patient-Clinician Interactions as a Predictor for Neuropsychological Tests Outcomes in Children: A Proof of Concept
Giulio Falcioni, Alexandra Georgescu, Emilia Molimpakis +3
This research report presents a proof-of-concept study on the application of machine learning techniques to video and speech data collected during diagnostic cognitive assessments…
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…
Speech and the n-Back task as a lens into depression. How combining both may allow us to isolate different core symptoms of depression
Salvatore Fara, Stefano Goria, Emilia Molimpakis +1
Embedded in any speech signal is a rich combination of cognitive, neuromuscular and physiological information. This richness makes speech a powerful signal in relation to a range o…
Handbook of LHC Higgs Cross Sections: 2. Differential Distributions
LHC Higgs Cross Section Working Group, S. Dittmaier, C. Mariotti +118
This Report summarises the results of the second year's activities of the LHC Higgs Cross Section Working Group. The main goal of the working group was to present the state of the…
The Higgs Boson Lineshape
Stefano Goria, Giampiero Passarino, Dario Rosco
The current searches for a heavy Higgs boson assume on-shell (stable) Higgs-boson production. The Higgs-boson production cross section is then sampled with a Breit-Wigner distribut…
Anomalous Threshold as the Pivot of Feynman Amplitudes
S. Goria, G. Passarino
Reduction techniques, Landau singularities and differential equations for Feynman amplitudes are briefly reviewed.