collaborators

6 papers

eess.AS2026

An Intervention-Based Framework for Shortcut Diagnosis in Spoofing Countermeasures

Santiago Rubio, Pilar Bello, Dayana Ribas +3

While deepfake audio detection systems achieve high performance in controlled benchmarks, their reliability often diminishes in the wild. Prior work shows that dataset-specific art…

eess.AS2026

Open-Set Source Tracing as Compositional Factors via Structured Prototypes

Santiago Rubio, Antonio Almudévar, Antonio Miguel +2

Recent research expands beyond binary anti-spoofing with the emergence of Source Tracing, the task of identifying the specific generative origins of synthetic speech. However, curr…

eess.AS2026

A Fair and Transparent Framework for Speech-Based Depression Detection: Balancing Interpretability and Performance

Mariel Estevez, Alfonso Ortega, Antonio Miguel +1

While speech provides rich, non-invasive biomarkers for mental-health assessment, clinical adoption is limited by opaque models and potential demographic bias. In this work we prop…

cs.LG2026

Rethinking Disentanglement under Dependent Factors of Variation

Antonio Almudévar, Alfonso Ortega

Representation learning is an approach that allows to discover and extract the factors of variation from the data. Intuitively, a representation is said to be disentangled if it se…

cs.SD2024

Audio-Visual Speaker Diarization: Current Databases, Approaches and Challenges

Victoria Mingote, Alfonso Ortega, Antonio Miguel +1

Nowadays, the large amount of audio-visual content available has fostered the need to develop new robust automatic speaker diarization systems to analyse and characterise it. This…

cs.LG2024

Predefined Prototypes for Intra-Class Separation and Disentanglement

Antonio Almudévar, Théo Mariotte, Alfonso Ortega +4

Prototypical Learning is based on the idea that there is a point (which we call prototype) around which the embeddings of a class are clustered. It has shown promising results in s…