4 accepted papers
The localization of sounding objects has been extensively studied. In certain situations, however, an object of interest may not emit sound while another sound source is active. For instance, this occurs when a silent human listens to music and needs to be localized, e.g., to optimize the playback f…
Attention-based models have become tremendously successful in the last couple of years for tasks such as Acoustic Scene Classification, Event Classification, or Speaker Identification. They operate on a set of tokens extracted from audio features and scale quadratically in sequence length due to the…
Disentanglement-based speaker anonymization involves decomposing speech into a semantically meaningful representation, altering the speaker embedding, and resynthesizing a waveform using a neural vocoder. State-of-the-art systems of this kind are known to remove emotion information. Possible reasons…
In an age of voice-enabled technology, voice anonymization offers a solution to protect people’s privacy, provided these systems work equally well across subgroups. This study investigates bias in voice anonymization systems within the context of the Voice Privacy Challenge. We curate a novel benchm…