5 accepted papers
Distributional shift is a central challenge in the deployment of machine learning models as they can be ill-equipped for real-world data. This is particularly evident in text-to-audio generation where the encoded representations are easily undermined by unseen prompts, which leads to the degradation…
Language modeling based music generation relies on discrete representations of audio frames. An audio frame (e.g. 20ms) is typically represented by a set of discrete codes (e.g. 4) computed by a neural codec. Autoregressive decoding typically generates a few thousands of codes per song, which is pro…
In this paper, we investigate template reconstruction attack of touchscreen biometrics, based on handwritten digits writer verification. In the event of a template database theft, we show that reconstructing the original drawn digit from the embeddings is possible without access to the original embe…
This paper investigates the use of recurrent neural networks to secure PIN code based authentication on smartphones, in a scenario where the user is invited to draw digits on the touchscreen. From the sequence of successive positions of the users finger on the touchscreen, a bidirectional recurrent…
This paper investigates single and cross-show diarization based on an unsupervised i-vector framework, on French TV and Radio corpora. This framework uses speaker clustering as a way to automatically select data from unlabeled corpora to train i-vector PLDA models. Performances between supervised an…