6 papers
Explaining a probabilistic prediction on the simplex with Shapley compositions
Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre +1
Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the predi…
Audio Question Answering with GRPO-Based Fine-Tuning and Calibrated Segment-Level Predictions
Marcel Gibier, Nolwenn Celton, Raphaël Duroselle +3
In this report, we describe our submission to Track 5 of the DCASE 2025 Challenge for the task of Audio Question Answering(AQA). Our system leverages the SSL backbone BEATs to extr…
Segmentwise Pruning in Audio-Language Models
Marcel Gibier, Raphaël Duroselle, Pierre Serrano +2
Recent audio-language models have shown impressive performance across a wide range of audio tasks and are increasingly capable of handling long audio inputs. However, the computing…
Improving Out-of-Domain Audio Deepfake Detection via Layer Selection and Fusion of SSL-Based Countermeasures
Pierre Serrano, Raphaël Duroselle, Florian Angulo +2
Audio deepfake detection systems based on frozen pre-trained self-supervised learning (SSL) encoders show a high level of performance when combined with layer-weighted pooling meth…
The distribution of calibrated likelihood functions on the probability-likelihood Aitchison simplex
Paul-Gauthier Noé, Andreas Nautsch, Driss Matrouf +2
While calibration of probabilistic predictions has been widely studied, this paper rather addresses calibration of likelihood functions. This has been discussed, especially in biom…
a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification
Hye-jin Shim, Jee-weon Jung, Tomi Kinnunen +3
Spoofing detection is today a mainstream research topic. Standard metrics can be applied to evaluate the performance of isolated spoofing detection solutions and others have been p…